--- /dev/null
+// Copyright (C) 2018-2020 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include <string>
+#include "ngraph_reader_tests.hpp"
+TEST_F(NGraphReaderTests, ReadGatherNDNetwork) {
+ std::string model = R"V0G0N(
+<net name="Network" version="10">
+ <layers>
+ <layer id="0" name="params_x" type="Parameter" version="opset1">
+ <data element_type="f32" shape="10,20,30"/>
+ <output>
+ <port id="0" precision="FP32">
+ <dim>10</dim>
+ <dim>20</dim>
+ <dim>30</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="1" name="indices_y" type="Parameter" version="opset1">
+ <data element_type="i32" shape="10,3,2"/>
+ <output>
+ <port id="0" precision="I32">
+ <dim>10</dim>
+ <dim>3</dim>
+ <dim>2</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="2" name="MyGatherND" type="GatherND" version="opset5">
+ <data batch_dims="0"/>
+ <input>
+ <port id="0">
+ <dim>10</dim>
+ <dim>20</dim>
+ <dim>30</dim>
+ </port>
+ <port id="1">
+ <dim>10</dim>
+ <dim>3</dim>
+ <dim>2</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32">
+ <dim>10</dim>
+ <dim>3</dim>
+ <dim>30</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="3" name="MyGatherND/sink_port_0" type="Result" version="opset1">
+ <input>
+ <port id="0">
+ <dim>10</dim>
+ <dim>3</dim>
+ <dim>30</dim>
+ </port>
+ </input>
+ </layer>
+ </layers>
+ <edges>
+ <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
+ <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
+ <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
+ </edges>
+</net>
+)V0G0N";
+ std::string modelV5 = R"V0G0N(
+<net name="Network" version="5" precision="FP32" batch="1">
+ <layers>
+ <layer id="0" name="params_x" type="Input" precision="FP32">
+ <output>
+ <port id="0" precision="FP32">
+ <dim>10</dim>
+ <dim>20</dim>
+ <dim>30</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="1" name="indices_y" type="Input" precision="I32">
+ <output>
+ <port id="0" precision="I32">
+ <dim>10</dim>
+ <dim>3</dim>
+ <dim>2</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="2" name="MyGatherND" type="GatherND" version="opset5">
+ <data batch_dims="0"/>
+ <input>
+ <port id="0">
+ <dim>10</dim>
+ <dim>20</dim>
+ <dim>30</dim>
+ </port>
+ <port id="1">
+ <dim>10</dim>
+ <dim>3</dim>
+ <dim>2</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32">
+ <dim>10</dim>
+ <dim>3</dim>
+ <dim>30</dim>
+ </port>
+ </output>
+ </layer>
+ </layers>
+ <edges>
+ <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
+ <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
+ </edges>
+</net>
+)V0G0N";
+
+ compareIRs(model, modelV5, 10);
+}
NGRAPH_SUPPRESS_DEPRECATED_START
using v0::GatherND;
NGRAPH_SUPPRESS_DEPRECATED_END
+
+ namespace v5
+ {
+ /// \brief GatherND operation
+ ///
+ class NGRAPH_API GatherND : public Op
+ {
+ public:
+ NGRAPH_RTTI_DECLARATION;
+ GatherND() = default;
+
+ /// \brief Constructs a GatherND operation.
+ ///
+ /// \param data Node producing data that are gathered
+ /// \param indices Node producing indices by which the operation gathers elements
+ /// or slices from data
+ /// \param batch_dims Specifies a number of batch dimensions
+ GatherND(const Output<Node>& data,
+ const Output<Node>& indices,
+ const size_t batch_dims = 0);
+
+ void validate_and_infer_types() override;
+ bool visit_attributes(AttributeVisitor& visitor) override;
+ virtual std::shared_ptr<Node>
+ clone_with_new_inputs(const OutputVector& new_args) const override;
+
+ size_t get_batch_dims() const { return m_batch_dims; }
+ private:
+ size_t m_batch_dims;
+ };
+ }
}
}
NGRAPH_OP(Swish, ngraph::op::v4)
// New operations added in opset5
+NGRAPH_OP(GatherND, ngraph::op::v5)
NGRAPH_OP(LogSoftmax, ngraph::op::v5)
NGRAPH_OP(LSTMSequence, ngraph::op::v5)
NGRAPH_OP(GRUSequence, ngraph::op::v5)
// vector = indices[leaf_vector_index]
// out[leaf_vector_index:] = params[vector]
template <typename T, typename U>
- void gather_nd(const T* params,
- const U* indices,
- T* out,
- const Shape& params_shape,
- const Shape& indices_shape,
- const Shape& out_shape)
+ void gather_nd_batch(const T* params,
+ const U* indices,
+ T* out,
+ const Shape& params_shape,
+ const Shape& indices_shape,
+ const Shape& out_shape)
{
using namespace std;
// Create a CoordinateTransform for "indices" that visits only the first element
out_coord_iter++;
}
}
+
+ template <typename T, typename U>
+ void gather_nd(const T* params,
+ const U* indices,
+ T* out,
+ const Shape& params_shape,
+ const Shape& indices_shape,
+ const Shape& out_shape,
+ int batch_dims = 0)
+ {
+ using namespace std;
+ if (batch_dims == 0)
+ {
+ gather_nd_batch(params, indices, out, params_shape, indices_shape, out_shape);
+ return;
+ }
+
+ size_t indices_ndim = static_cast<size_t>(indices_shape.size());
+ Coordinate indices_outer_start_corner(indices_ndim, 0);
+ Coordinate indices_outer_end_corner(indices_shape);
+ for (size_t i = batch_dims; i < indices_ndim; i++)
+ {
+ indices_outer_end_corner[i] = 1;
+ }
+ Strides indices_strides(indices_ndim, 1);
+ AxisVector indices_axis_order(indices_ndim);
+ std::iota(indices_axis_order.begin(), indices_axis_order.end(), 0);
+ CoordinateTransform indices_outer_transform(indices_shape,
+ indices_outer_start_corner,
+ indices_outer_end_corner,
+ indices_strides,
+ indices_axis_order);
+
+ size_t params_ndim = static_cast<size_t>(params_shape.size());
+ Coordinate params_outer_start_corner(params_ndim, 0);
+ Coordinate params_outer_end_corner(params_shape);
+ for (size_t i = batch_dims; i < params_ndim; i++)
+ {
+ params_outer_end_corner[i] = 1;
+ }
+ Strides params_strides(params_ndim, 1);
+ AxisVector params_axis_order(params_ndim);
+ std::iota(params_axis_order.begin(), params_axis_order.end(), 0);
+ CoordinateTransform params_outer_transform(params_shape,
+ params_outer_start_corner,
+ params_outer_end_corner,
+ params_strides,
+ params_axis_order);
+
+ size_t out_ndim = static_cast<size_t>(out_shape.size());
+ Coordinate out_start_corner(out_ndim, 0);
+ Coordinate out_end_corner(out_shape);
+ for (size_t i = 1; i < out_ndim; i++)
+ {
+ out_end_corner[i] = 1;
+ }
+ Strides out_strides(out_ndim, 1);
+ AxisVector out_axis_order(out_ndim);
+ std::iota(out_axis_order.begin(), out_axis_order.end(), 0);
+ CoordinateTransform out_transform(
+ out_shape, out_start_corner, out_end_corner, out_strides, out_axis_order);
+
+ Shape indices_shape_batch(indices_shape.begin() + batch_dims, indices_shape.end());
+ Shape params_shape_batch(params_shape.begin() + batch_dims, params_shape.end());
+ Shape output_shape_batch(out_shape.begin() + 1, out_shape.end());
+ auto out_coord_iter = out_transform.begin();
+ auto params_coord_iter = params_outer_transform.begin();
+ for (const Coordinate& indices_coord : indices_outer_transform)
+ {
+ auto indices_index = indices_outer_transform.index(indices_coord);
+ auto params_index = params_outer_transform.index(*params_coord_iter);
+ auto output_index = out_transform.index(*out_coord_iter);
+ gather_nd_batch(params + params_index,
+ indices + indices_index,
+ out + output_index,
+ params_shape_batch,
+ indices_shape_batch,
+ output_shape_batch);
+
+ out_coord_iter++;
+ params_coord_iter++;
+ }
+ }
}
}
}
#include "ngraph/op/gather_nd.hpp"
#include "ngraph/shape.hpp"
-NGRAPH_SUPPRESS_DEPRECATED_START
-
using namespace std;
using namespace ngraph;
+// ------------------------------ V5 ------------------------------
+
+NGRAPH_RTTI_DEFINITION(op::v5::GatherND, "GatherND", 5);
+
+op::v5::GatherND::GatherND(const Output<Node>& data,
+ const Output<Node>& indices,
+ const size_t batch_dims)
+ : Op({data, indices})
+ , m_batch_dims(batch_dims)
+{
+ constructor_validate_and_infer_types();
+}
+
+void op::v5::GatherND::validate_and_infer_types()
+{
+ // check types of input tensors
+ const auto& data_type = get_input_element_type(0);
+ const auto& indices_type = get_input_element_type(1);
+
+ NODE_VALIDATION_CHECK(this,
+ indices_type.is_integral_number(),
+ "The indices type is expected to be an integer type. Got: ",
+ indices_type);
+
+ // check ranks of input tensors
+ const auto& data_pshape = get_input_partial_shape(0);
+ const auto& indices_pshape = get_input_partial_shape(1);
+
+ if (data_pshape.rank().is_static())
+ {
+ NODE_VALIDATION_CHECK(
+ this, data_pshape.rank().get_length() > 0, "Data rank must be at least 1.");
+
+ NODE_VALIDATION_CHECK(this,
+ data_pshape.rank().get_length() > m_batch_dims,
+ "Number of batch dimensions must not exceed a rank of data.");
+ }
+
+ if (indices_pshape.rank().is_static())
+ {
+ NODE_VALIDATION_CHECK(
+ this, indices_pshape.rank().get_length() > 0, "Indices rank must be at least 1.");
+
+ NODE_VALIDATION_CHECK(this,
+ indices_pshape.rank().get_length() > m_batch_dims,
+ "Number of batch dimensions must not exceed a rank of indices.");
+ }
+
+ if (data_pshape.rank().is_static() && indices_pshape.rank().is_static())
+ {
+ // check that batch dimensions of data and indices are the same
+ for (auto batch_dim = 0; batch_dim < m_batch_dims; batch_dim++)
+ {
+ if (data_pshape[batch_dim].is_static() && indices_pshape[batch_dim].is_static())
+ {
+ NODE_VALIDATION_CHECK(this,
+ data_pshape[batch_dim].get_length() ==
+ indices_pshape[batch_dim].get_length(),
+ "Batch dimensions of data and indices must be the same.");
+ }
+ }
+
+ if (indices_pshape[indices_pshape.rank().get_length() - 1].is_static())
+ {
+ NODE_VALIDATION_CHECK(
+ this,
+ (indices_pshape[indices_pshape.rank().get_length() - 1].get_length() +
+ m_batch_dims) <= data_pshape.rank().get_length(),
+ "Length of a tuple with indices must not exceed a rank of data tensor excluding "
+ "batch dimensions.");
+ }
+ }
+
+ // set output shape
+ set_output_size(1);
+ if (data_pshape.rank().is_static() && indices_pshape.rank().is_static() &&
+ indices_pshape[indices_pshape.rank().get_length() - 1].is_static())
+ {
+ auto indices_tuple_length =
+ indices_pshape[indices_pshape.rank().get_length() - 1].get_length();
+ auto slice_length = data_pshape.rank().get_length() - indices_tuple_length - m_batch_dims;
+ auto output_indices_length = indices_pshape.rank().get_length() - m_batch_dims - 1;
+ auto output_rank = output_indices_length + slice_length;
+ size_t delta_output_rank = 0;
+ if (m_batch_dims > 0)
+ {
+ delta_output_rank = 1;
+ }
+ std::vector<Dimension> output_shape(output_rank + delta_output_rank);
+ if (m_batch_dims > 0)
+ {
+ output_shape[0] = 1;
+ for (auto dim = 0; dim < m_batch_dims; dim++)
+ {
+ if (data_pshape[dim].is_static())
+ {
+ output_shape[0] *= data_pshape[dim].get_length();
+ }
+ else if (indices_pshape[dim].is_static())
+ {
+ output_shape[0] *= indices_pshape[dim].get_length();
+ }
+ else
+ {
+ output_shape[0] = Dimension::dynamic();
+ break;
+ }
+ }
+ }
+ for (auto dim = 0; dim < output_indices_length; dim++)
+ {
+ output_shape[dim + delta_output_rank] = indices_pshape[dim + m_batch_dims];
+ }
+ for (auto dim = 0; dim < slice_length; dim++)
+ {
+ output_shape[output_indices_length + dim + delta_output_rank] =
+ data_pshape[m_batch_dims + indices_tuple_length + dim];
+ }
+ set_output_type(0, data_type, PartialShape(output_shape));
+ }
+ else
+ {
+ set_output_type(0, data_type, PartialShape{Dimension::dynamic()});
+ }
+}
+
+bool op::v5::GatherND::visit_attributes(AttributeVisitor& visitor)
+{
+ visitor.on_attribute("batch_dims", m_batch_dims);
+ return true;
+}
+
+shared_ptr<Node> op::v5::GatherND::clone_with_new_inputs(const OutputVector& new_args) const
+{
+ check_new_args_count(this, new_args);
+ return make_shared<op::v5::GatherND>(new_args.at(0), new_args.at(1), m_batch_dims);
+}
+
+// ------------------------------ V0 ------------------------------
+
+NGRAPH_SUPPRESS_DEPRECATED_START
+
static int PARAMS = 0;
static int INDICES = 1;
from ngraph.opset5 import floor
from ngraph.opset5 import floor_mod
from ngraph.opset5 import gather
+from ngraph.opset5 import gather_nd
from ngraph.opset5 import gather_tree
from ngraph.opset5 import gelu
from ngraph.opset5 import greater
from ngraph.opset1.ops import floor
from ngraph.opset1.ops import floor_mod
from ngraph.opset1.ops import gather
+from ngraph.opset5.ops import gather_nd
from ngraph.opset1.ops import gather_tree
from ngraph.opset2.ops import gelu
from ngraph.opset1.ops import greater
@nameable_op
+def gather_nd(
+ data: NodeInput,
+ indices: NodeInput,
+ batch_dims: Optional[int] = 0,
+ name: Optional[str] = None,
+) -> Node:
+ """Return a node which performs GatherND.
+
+ :param data: N-D tensor with data for gathering
+ :param indices: K-D tensor of tuples with indices by which data is gathered
+ :param batch_dims: Scalar value of batch dimensions
+ :return: The new node which performs GatherND
+ """
+ inputs = as_nodes(data, indices)
+
+ attributes = {
+ "batch_dims": batch_dims
+ }
+
+ return _get_node_factory_opset5().create("GatherND", inputs, attributes)
+
+
+@nameable_op
def log_softmax(data: NodeInput, axis: int, name: Optional[str] = None) -> Node:
"""Apply LogSoftmax operation on each element of input tensor.
return it->second();
}
- const ngraph::OpSet& m_opset{ngraph::get_opset4()};
+ const ngraph::OpSet& m_opset{ngraph::get_opset5()};
};
}
import pytest
import ngraph as ng
+from ngraph.impl import Type
from tests.runtime import get_runtime
from tests.test_ngraph.util import run_op_node
result = run_op_node([cond, then_node, else_node], ng.select)
assert np.allclose(result, excepted)
+
+
+def test_gather_nd():
+ indices_type = np.int32
+ data_dtype = np.float32
+ data = ng.parameter([2, 10, 80, 30, 50], dtype=data_dtype, name="data")
+ indices = ng.parameter([2, 10, 30, 40, 2], dtype=indices_type, name="indices")
+ batch_dims = 2
+ expected_shape = [20, 30, 40, 50]
+
+ node = ng.gather_nd(data, indices, batch_dims)
+ assert node.get_type_name() == "GatherND"
+ assert node.get_output_size() == 1
+ assert list(node.get_output_shape(0)) == expected_shape
+ assert node.get_output_element_type(0) == Type.f32
backend/function_name.in.cpp
backend/fused_op.in.cpp
backend/gather.in.cpp
+ backend/gather_nd.in.cpp
backend/gelu.in.cpp
backend/group_convolution.in.cpp
backend/interpolate.in.cpp
(vector<float>{1.0f, 2.0f, 3.0f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
}
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_single_indices)
-{
- Shape params_shape{3, 3};
- Shape indices_shape{2};
- Shape out_shape{};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 1.4f, 1.5f, 1.6f, 1.7f, 1.8f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{1, 2});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f(
- (vector<float>{1.5f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_scalar_from_2d)
-{
- Shape params_shape{2, 2};
- Shape indices_shape{2, 2};
- Shape out_shape{2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{0, 0, 1, 1});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f(
- (vector<float>{1.0f, 1.3f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_1d_from_2d)
-{
- Shape params_shape{2, 2};
- Shape indices_shape{2, 1};
- Shape out_shape{2, 2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{1, 0});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}),
- read_vector<float>(result),
- MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_scalar_from_3d)
-{
- Shape params_shape{2, 2, 2};
- Shape indices_shape{2, 3};
- Shape out_shape{2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{0, 0, 1, 1, 0, 1});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f(
- (vector<float>{1.1f, 2.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_1d_from_3d)
-{
- Shape params_shape{2, 2, 2};
- Shape indices_shape{2, 2};
- Shape out_shape{2, 2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{0, 1, 1, 0});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f}),
- read_vector<float>(result),
- MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_2d_from_3d)
-{
- Shape params_shape{2, 2, 2};
- Shape indices_shape{1, 1};
- Shape out_shape{1, 2, 2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{1});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f}),
- read_vector<float>(result),
- MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_scalar_from_2d)
-{
- Shape params_shape{2, 2};
- Shape indices_shape{2, 1, 2};
- Shape out_shape{2, 1};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{0, 0, 0, 1});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f(
- (vector<float>{1.0f, 1.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_1d_from_2d)
-{
- Shape params_shape{2, 2};
- Shape indices_shape{2, 1, 1};
- Shape out_shape{2, 1, 2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{1, 0});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}),
- read_vector<float>(result),
- MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_scalar_from_3d)
-{
- Shape params_shape{2, 2, 2};
- Shape indices_shape{2, 2, 3};
- Shape out_shape{2, 2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f((vector<float>{1.1f, 2.1f, 1.3f, 2.2f}),
- read_vector<float>(result),
- MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_1d_from_3d)
-{
- Shape params_shape{2, 2, 2};
- Shape indices_shape{2, 2, 2};
- Shape out_shape{2, 2, 2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{0, 1, 1, 0, 0, 0, 1, 1});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f, 1.0f, 1.1f, 2.2f, 2.3f}),
- read_vector<float>(result),
- MIN_FLOAT_TOLERANCE_BITS));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_2d_from_3d)
-{
- Shape params_shape{2, 2, 2};
- Shape indices_shape{2, 1, 1};
- Shape out_shape{2, 1, 2, 2};
- auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
- auto f = make_shared<Function>(G, ParameterVector{P, I});
-
- auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
- // Create some tensors for input/output
- auto p = backend->create_tensor(element::f32, params_shape);
- copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
- auto i = backend->create_tensor(element::i32, indices_shape);
- copy_data(i, vector<int32_t>{1, 0});
- auto result = backend->create_tensor(element::f32, out_shape);
-
- auto c = backend->compile(f);
- c->call_with_validate({result}, {p, i});
- EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f, 1.0f, 1.1f, 1.2f, 1.3f}),
- read_vector<float>(result),
- MIN_FLOAT_TOLERANCE_BITS));
-}
-
NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_int8)
{
Shape params_shape{3, 2};
--- /dev/null
+//*****************************************************************************
+// Copyright 2017-2020 Intel Corporation
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//*****************************************************************************
+
+#include <algorithm>
+#include <cinttypes>
+#include <cmath>
+#include <cstdlib>
+#include <random>
+#include <string>
+
+#include "gtest/gtest.h"
+#include "ngraph/ngraph.hpp"
+#include "ngraph/runtime/tensor.hpp"
+#include "runtime/backend.hpp"
+#include "util/all_close.hpp"
+#include "util/all_close_f.hpp"
+#include "util/ndarray.hpp"
+#include "util/random.hpp"
+#include "util/test_case.hpp"
+#include "util/test_control.hpp"
+#include "util/test_tools.hpp"
+
+NGRAPH_SUPPRESS_DEPRECATED_START
+
+using namespace std;
+using namespace ngraph;
+
+static string s_manifest = "${MANIFEST}";
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_single_indices)
+{
+ Shape params_shape{3, 3};
+ Shape indices_shape{2};
+ Shape out_shape{};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 1.4f, 1.5f, 1.6f, 1.7f, 1.8f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1, 2});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.5f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.5f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_scalar_from_2d)
+{
+ Shape params_shape{2, 2};
+ Shape indices_shape{2, 2};
+ Shape out_shape{2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{0, 0, 1, 1});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.0f, 1.3f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.0f, 1.3f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_1d_from_2d)
+{
+ Shape params_shape{2, 2};
+ Shape indices_shape{2, 1};
+ Shape out_shape{2, 2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1, 0});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_scalar_from_3d)
+{
+ Shape params_shape{2, 2, 2};
+ Shape indices_shape{2, 3};
+ Shape out_shape{2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{0, 0, 1, 1, 0, 1});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.1f, 2.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.1f, 2.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_1d_from_3d)
+{
+ Shape params_shape{2, 2, 2};
+ Shape indices_shape{2, 2};
+ Shape out_shape{2, 2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{0, 1, 1, 0});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_2d_from_3d)
+{
+ Shape params_shape{2, 2, 2};
+ Shape indices_shape{1, 1};
+ Shape out_shape{1, 2, 2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_scalar_from_2d)
+{
+ Shape params_shape{2, 2};
+ Shape indices_shape{2, 1, 2};
+ Shape out_shape{2, 1};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{0, 0, 0, 1});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.0f, 1.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{1.0f, 1.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_1d_from_2d)
+{
+ Shape params_shape{2, 2};
+ Shape indices_shape{2, 1, 1};
+ Shape out_shape{2, 1, 2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1, 0});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_scalar_from_3d)
+{
+ Shape params_shape{2, 2, 2};
+ Shape indices_shape{2, 2, 3};
+ Shape out_shape{2, 2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.1f, 2.1f, 1.3f, 2.2f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.1f, 2.1f, 1.3f, 2.2f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_1d_from_3d)
+{
+ Shape params_shape{2, 2, 2};
+ Shape indices_shape{2, 2, 2};
+ Shape out_shape{2, 2, 2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{0, 1, 1, 0, 0, 0, 1, 1});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f, 1.0f, 1.1f, 2.2f, 2.3f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f, 1.0f, 1.1f, 2.2f, 2.3f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_2d_from_3d)
+{
+ Shape params_shape{2, 2, 2};
+ Shape indices_shape{2, 1, 1};
+ Shape out_shape{2, 1, 2, 2};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::GatherND>(P, I);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1, 0});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f, 1.0f, 1.1f, 1.2f, 1.3f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ auto f5 = make_shared<Function>(G5, ParameterVector{P, I});
+ auto c5 = backend->compile(f5);
+ c5->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f, 1.0f, 1.1f, 1.2f, 1.3f}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_dims1)
+{
+ Shape params_shape{2, 3, 4};
+ Shape indices_shape{2, 1};
+ Shape out_shape{2, 4};
+ int batch_dims = 1;
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::v5::GatherND>(P, I, batch_dims);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
+ 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1, 0});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{5, 6, 7, 8, 13, 14, 15, 16}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_dims2)
+{
+ Shape params_shape{2, 3, 4, 2};
+ Shape indices_shape{2, 3, 3, 2};
+ Shape out_shape{6, 3};
+ int batch_dims = 2;
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::v5::GatherND>(P, I, batch_dims);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
+ 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
+ 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1, 0, 3, 1, 2, 1, 0, 1, 1, 1, 2, 0, 3, 0, 3, 1, 2, 1,
+ 2, 0, 1, 1, 3, 1, 1, 1, 2, 0, 2, 0, 0, 0, 3, 1, 3, 1});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f(
+ (vector<float>{3, 8, 6, 10, 12, 13, 23, 24, 22, 29, 28, 32, 36, 37, 37, 41, 48, 48}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_dims2_lead_dims)
+{
+ Shape params_shape{2, 3, 4};
+ Shape indices_shape{2, 3, 1, 1};
+ Shape out_shape{6, 1};
+ int batch_dims = 2;
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G = make_shared<op::v5::GatherND>(P, I, batch_dims);
+ auto f = make_shared<Function>(G, ParameterVector{P, I});
+
+ auto backend = runtime::Backend::create("${BACKEND_NAME}");
+
+ // Create some tensors for input/output
+ auto p = backend->create_tensor(element::f32, params_shape);
+ copy_data(p, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
+ 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24});
+ auto i = backend->create_tensor(element::i32, indices_shape);
+ copy_data(i, vector<int32_t>{1, 0, 2, 0, 2, 2});
+ auto result = backend->create_tensor(element::f32, out_shape);
+
+ auto c = backend->compile(f);
+ c->call_with_validate({result}, {p, i});
+ EXPECT_TRUE(test::all_close_f((vector<float>{2, 5, 11, 13, 19, 23}),
+ read_vector<float>(result),
+ MIN_FLOAT_TOLERANCE_BITS));
+}
gather_nd_batch_scalar_from_3d
gather_nd_batch_1d_from_3d
gather_nd_batch_2d_from_3d
+gather_nd_batch_dims1
+gather_nd_batch_dims2
+gather_nd_batch_dims2_lead_dims
# Cannot cast ngraph node Stack to CNNLayer!
stack_matrix_rowise
}
break;
}
+ case OP_TYPEID::GatherND_v5:
+ {
+ const op::v5::GatherND* gatherNDNode = static_cast<const op::v5::GatherND*>(&node);
+ if (node.get_input_element_type(1) == element::i64)
+ {
+ reference::gather_nd<T, int64_t>(args[0]->get_data_ptr<T>(),
+ args[1]->get_data_ptr<int64_t>(),
+ out[0]->get_data_ptr<T>(),
+ node.get_input_shape(0),
+ node.get_input_shape(1),
+ node.get_output_shape(0),
+ gatherNDNode->get_batch_dims());
+ }
+ else if (node.get_input_element_type(1) == element::i32)
+ {
+ reference::gather_nd<T, int32_t>(args[0]->get_data_ptr<T>(),
+ args[1]->get_data_ptr<int32_t>(),
+ out[0]->get_data_ptr<T>(),
+ node.get_input_shape(0),
+ node.get_input_shape(1),
+ node.get_output_shape(0),
+ gatherNDNode->get_batch_dims());
+ }
+ else
+ {
+ throw ngraph_error("Unexpected type");
+ }
+ break;
+ }
case OP_TYPEID::GRUCell_v3:
{
const op::v3::GRUCell* gru_cell = static_cast<const op::v3::GRUCell*>(&node);
#undef ID_SUFFIX
#define ID_SUFFIX(NAME) NAME##_v5
+NGRAPH_OP(GatherND, op::v5)
NGRAPH_OP(LSTMSequence, op::v5)
NGRAPH_OP(GRUSequence, op::v5)
NGRAPH_OP(RNNSequence, op::v5)
#include "ngraph/ngraph.hpp"
#include "util/type_prop.hpp"
-NGRAPH_SUPPRESS_DEPRECATED_START
-
using namespace std;
using namespace ngraph;
+// ------------------------------ V5 ------------------------------
+
+TEST(type_prop, gather_nd_slices_from_4d_batch_dims0)
+{
+ Shape params_shape{2, 3, 11, 12};
+ Shape indices_shape{2, 3, 2};
+ Shape out_shape{2, 3, 11, 12};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 0);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
+}
+
+TEST(type_prop, gather_nd_scalars_from_4d_batch_dims2)
+{
+ Shape params_shape{2, 3, 11, 12};
+ Shape indices_shape{2, 3, 2};
+ Shape out_shape{6};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 2);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
+}
+
+TEST(type_prop, gather_nd_slices_from_5d_batch_dims2)
+{
+ Shape params_shape{7, 5, 11, 12, 32};
+ Shape indices_shape{7, 5, 3, 1};
+ Shape out_shape{35, 3, 12, 32};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 2);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
+}
+
+TEST(type_prop, gather_nd_batch_dim2_with_dyn_dim)
+{
+ PartialShape params_shape{7, Dimension::dynamic(), 11, 12, 32};
+ Shape indices_shape{7, 5, 3, 1};
+ Shape out_shape{35, 3, 12, 32};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 2);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
+}
+
+TEST(type_prop, gather_nd_batch_dim2_with_dyn_dim2)
+{
+ PartialShape params_shape{7, Dimension::dynamic(), Dimension::dynamic(), 12, 32};
+ Shape indices_shape{7, 5, 3, 1};
+ Shape out_shape{35, 3, 12, 32};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 2);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
+}
+
+TEST(type_prop, gather_nd_batch_dim2_with_dyn_dim3)
+{
+ PartialShape params_shape{
+ 7, Dimension::dynamic(), Dimension::dynamic(), 12, Dimension::dynamic()};
+ Shape indices_shape{7, 5, 3, 1};
+ PartialShape out_shape{35, 3, 12, Dimension::dynamic()};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 2);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_TRUE(G5->get_output_partial_shape(0).same_scheme(out_shape));
+}
+
+TEST(type_prop, gather_nd_fail_batch_dims_greater_indices_rank)
+{
+ Shape params_shape{2, 3, 4, 5};
+ Shape indices_shape{2, 1};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+
+ try
+ {
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 3);
+ // Should have thrown, so fail if it didn't
+ FAIL() << "Incorrect indices rank";
+ }
+ catch (const NodeValidationFailure& error)
+ {
+ EXPECT_HAS_SUBSTRING(
+ error.what(),
+ std::string("Number of batch dimensions must not exceed a rank of indices."));
+ }
+ catch (...)
+ {
+ FAIL() << "Deduced type check failed for unexpected reason";
+ }
+}
+
+TEST(type_prop, gather_nd_fail_unequal_batch_dims)
+{
+ Shape params_shape{2, 3, 4, 5};
+ Shape indices_shape{2, 1, 4};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+
+ try
+ {
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 2);
+ // Should have thrown, so fail if it didn't
+ FAIL() << "Incorrect indices rank";
+ }
+ catch (const NodeValidationFailure& error)
+ {
+ EXPECT_HAS_SUBSTRING(error.what(),
+ std::string("Batch dimensions of data and indices must be the same."));
+ }
+ catch (...)
+ {
+ FAIL() << "Deduced type check failed for unexpected reason";
+ }
+}
+
+TEST(type_prop, gather_nd_fail_indices_tuple_greater_data_rank_batch_dims2)
+{
+ Shape params_shape{2, 1, 4, 5};
+ Shape indices_shape{2, 1, 5, 3};
+ auto P = make_shared<op::Parameter>(element::f32, params_shape);
+ auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+
+ try
+ {
+ auto G5 = make_shared<op::v5::GatherND>(P, I, 2);
+ // Should have thrown, so fail if it didn't
+ FAIL() << "Incorrect indices rank";
+ }
+ catch (const NodeValidationFailure& error)
+ {
+ EXPECT_HAS_SUBSTRING(error.what(),
+ std::string("Length of a tuple with indices must not exceed a rank of "
+ "data tensor excluding batch dimensions."));
+ }
+ catch (...)
+ {
+ FAIL() << "Deduced type check failed for unexpected reason";
+ }
+}
+
+// ------------------------------ V0 + V5 ------------------------------
+
TEST(type_prop, gather_nd_scalar_from_2d)
{
Shape params_shape{2, 2};
Shape out_shape{2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_1d_from_2d)
Shape out_shape{2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_scalar_from_3d)
Shape out_shape{2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_1d_from_3d)
Shape out_shape{2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_2d_from_3d)
Shape out_shape{1, 2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_batch_scalar_from_2d)
Shape out_shape{2, 1};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_batch_1d_from_2d)
Shape out_shape{2, 1, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_batch_scalar_from_3d)
Shape out_shape{2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_batch_1d_from_3d)
Shape out_shape{2, 2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_batch_2d_from_3d)
Shape out_shape{2, 1, 2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
- auto G = make_shared<op::GatherND>(P, I);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
+ auto G = make_shared<op::v0::GatherND>(P, I);
ASSERT_EQ(G->get_element_type(), element::f32);
ASSERT_EQ(G->get_shape(), out_shape);
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ ASSERT_EQ(G5->get_element_type(), element::f32);
+ ASSERT_EQ(G5->get_shape(), out_shape);
}
TEST(type_prop, gather_nd_fail_params_rank)
Shape out_shape{2, 1, 2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
try
{
- auto G = make_shared<op::GatherND>(P, I);
+ auto G = make_shared<op::v0::GatherND>(P, I);
// Should have thrown, so fail if it didn't
FAIL() << "Incorrect params rank";
}
{
FAIL() << "Deduced type check failed for unexpected reason";
}
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ try
+ {
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ // Should have thrown, so fail if it didn't
+ FAIL() << "Incorrect params rank";
+ }
+ catch (const NodeValidationFailure& error)
+ {
+ EXPECT_HAS_SUBSTRING(error.what(), std::string("Data rank must be at least 1."));
+ }
+ catch (...)
+ {
+ FAIL() << "Deduced type check failed for unexpected reason";
+ }
}
TEST(type_prop, gather_nd_fail_indices_rank)
Shape out_shape{2, 1, 2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
auto I = make_shared<op::Parameter>(element::i32, indices_shape);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
try
{
- auto G = make_shared<op::GatherND>(P, I);
+ auto G = make_shared<op::v0::GatherND>(P, I);
// Should have thrown, so fail if it didn't
FAIL() << "Incorrect indices rank";
}
{
FAIL() << "Deduced type check failed for unexpected reason";
}
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ try
+ {
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ // Should have thrown, so fail if it didn't
+ FAIL() << "Incorrect indices rank";
+ }
+ catch (const NodeValidationFailure& error)
+ {
+ EXPECT_HAS_SUBSTRING(error.what(), std::string("Indices rank must be at least 1."));
+ }
+ catch (...)
+ {
+ FAIL() << "Deduced type check failed for unexpected reason";
+ }
}
TEST(type_prop, gather_nd_fail_indices_element_type)
Shape indices_shape{2, 1, 1};
Shape out_shape{2, 1, 2, 2};
auto P = make_shared<op::Parameter>(element::f32, params_shape);
- auto I = make_shared<op::Parameter>(element::i16, indices_shape);
+ auto I = make_shared<op::Parameter>(element::f32, indices_shape);
+
+ NGRAPH_SUPPRESS_DEPRECATED_START
try
{
- auto G = make_shared<op::GatherND>(P, I);
+ auto G = make_shared<op::v0::GatherND>(P, I);
// Should have thrown, so fail if it didn't
FAIL() << "Incorrect indices element type";
}
{
FAIL() << "Deduced type check failed for unexpected reason";
}
+ NGRAPH_SUPPRESS_DEPRECATED_END
+
+ try
+ {
+ auto G5 = make_shared<op::v5::GatherND>(P, I);
+ // Should have thrown, so fail if it didn't
+ FAIL() << "Incorrect indices element type";
+ }
+ catch (const NodeValidationFailure& error)
+ {
+ EXPECT_HAS_SUBSTRING(error.what(),
+ std::string("The indices type is expected to be an integer type."));
+ }
+ catch (...)
+ {
+ FAIL() << "Deduced type check failed for unexpected reason";
+ }
}
projects / platform / upstream / dldt.git / commitdiff