Add transpose conv gtest (#5391)

* Add transpose conv gtest

Add transpose conv gtest
- stride: 2
- same padding

Signed-off-by: Hyeongseok Oh <hseok82.oh@samsung.com>
* Update skiplist

diff --git a/tests/nnapi/nnapi_gtest.skip.armv7l-linux b/tests/nnapi/nnapi_gtest.skip.armv7l-linux
index c81277a..a444521 100644 (file)
--- a/tests/nnapi/nnapi_gtest.skip.armv7l-linux
+++ b/tests/nnapi/nnapi_gtest.skip.armv7l-linux
@@ -12,6 +12,7 @@ GeneratedTests.prelu_ex_quant8_1
 GeneratedTests.prelu_ex_broadcast_quant8_1
 # Unexpected result
 GeneratedTests.pack*
+GeneratedTests.transpose_conv_ex_float_4
 # Not support broadcast
 GeneratedTests.logical_or_ex_broadcast_4D_2D
 # Unsupported optional input that has shape

diff --git a/tests/nnapi/nnapi_gtest.skip.armv7l-linux.pacl b/tests/nnapi/nnapi_gtest.skip.armv7l-linux.pacl
index 3606270..25833b9 100644 (file)
--- a/tests/nnapi/nnapi_gtest.skip.armv7l-linux.pacl
+++ b/tests/nnapi/nnapi_gtest.skip.armv7l-linux.pacl
@@ -18,6 +18,7 @@ GeneratedTests.prelu_ex_broadcast_quant8_1
 GeneratedTests.svdf
 GeneratedTests.svdf2
 GeneratedTests.svdf_state
+GeneratedTests.transpose_conv_ex_float_4
 ValidationTestCompilation.CreateExecution
 ValidationTestCompilation.Finish
 ValidationTestCompilation.SetPreference

diff --git a/tests/nnapi/nnapi_gtest.skip.armv7l-tizen b/tests/nnapi/nnapi_gtest.skip.armv7l-tizen
index a188c28..7601458 100644 (file)
--- a/tests/nnapi/nnapi_gtest.skip.armv7l-tizen
+++ b/tests/nnapi/nnapi_gtest.skip.armv7l-tizen
@@ -28,6 +28,7 @@ GeneratedTests.prelu_ex*
 GeneratedTests.svdf
 GeneratedTests.svdf2
 GeneratedTests.svdf_state
+GeneratedTests.transpose_conv_ex_float_4
 ValidationTestCompilation.CreateExecution
 ValidationTestCompilation.Finish
 ValidationTestCompilation.SetPreference

diff --git a/tests/nnapi/specs/Ex/transpose_conv_ex_float_4.mod.py b/tests/nnapi/specs/Ex/transpose_conv_ex_float_4.mod.py
new file mode 100644 (file)
index 0000000..71383b4
--- /dev/null
+++ b/tests/nnapi/specs/Ex/transpose_conv_ex_float_4.mod.py
@@ -0,0 +1,56 @@
+# model
+model = Model()
+i0 = Input("op_shape", "TENSOR_INT32", "{4}")
+weights = Input("ker", "TENSOR_FLOAT32", "{1, 3, 3, 1}")
+i1 = Input("in", "TENSOR_FLOAT32", "{1, 4, 4, 1}" )
+pad = Int32Scalar("pad_same", 1)
+s_x = Int32Scalar("stride_x", 2)
+s_y = Int32Scalar("stride_y", 2)
+i2 = Output("op", "TENSOR_FLOAT32", "{1, 8, 8, 1}")
+model = model.Operation("TRANSPOSE_CONV_EX", i0, weights, i1, pad, s_x, s_y).To(i2)
+
+batch = 1
+in_chans = 1
+out_chans = 1
+in_rows = 4
+in_cols = 4
+out_rows = 8
+out_cols = 8
+ker_rows = 3
+ker_cols = 3
+stride = 2
+# pad is 0 (left: 0  right: 1 top: 0 bottom: 1)
+input_table = [x for x in range(batch * in_rows * in_cols * in_chans)]
+kernel_table = [x for x in range(out_chans * ker_rows * ker_cols * in_chans)]
+out_table = [0 for x in range(batch * out_rows * out_cols * out_chans)]
+
+for i in range(batch):
+  for j in range(in_rows):
+    for k in range(in_cols):
+      for l in range(in_chans):
+        out_row_origin = j * stride
+        out_col_origin = k * stride
+        input_value = input_table[((i * in_rows + j) * in_cols + k) * in_chans + l]
+
+        for m in range(ker_rows):
+          for n in range(ker_cols):
+            for o in range(out_chans):
+              out_row = out_row_origin + m
+              out_col = out_col_origin + n
+              if (out_row < out_rows) and (out_col < out_cols) and (out_row >= 0) and (out_col >= 0):
+                kernel_value = kernel_table[((o * ker_rows + m) * ker_cols + n) * in_chans + l]
+                out_table[((i * out_rows + out_row) * out_cols + out_col) * out_chans + o] += (input_value * kernel_value)
+
+# Example 1. Input in operand 0,
+input0 = {i0:  # output shape
+          [1, 8, 8, 1],
+          i1:  # input 0
+          input_table,
+          weights:  # input 1
+          kernel_table}
+
+output0 = {i2:  # output 0
+           out_table}
+
+# Instantiate an example
+Example((input0, output0))