identity_list=None,
convert_map=None):
"""Convert from Caffe2 operator to nnvm operator.
- The converter must specify conversions explicity for incompatible name, and
+ The converter must specify conversions explicitly for incompatible name, and
apply handlers to operator attributes.
Parameters
identity_list=None,
convert_map=None):
"""Convert from onnx operator to nnvm operator.
- The converter must specify conversions explicity for incompatible name, and
+ The converter must specify conversions explicitly for incompatible name, and
apply handlers to operator attributes.
Parameters
def _convert_operator(self, op_name, inputs, attrs,
graph, identity_list=None, convert_map=None):
"""Convert from Tensorflow operator to nnvm operator.
- The converter must specify conversions explicity for incompatible name, and
+ The converter must specify conversions explicitly for incompatible name, and
apply handlers to operator attributes.
Parameters
def test_forward_clip():
data = mx.sym.var('data')
- data = mx.sym.concat(data, -data, dim=1) # negative part explicity
+ data = mx.sym.concat(data, -data, dim=1) # negative part explicitly
mx_sym = mx.sym.clip(data, a_min=0, a_max=1)
verify_mxnet_frontend_impl(mx_sym, (1, 3, 100, 100), (1, 6, 100, 100))
class Expr(ExprOp, NodeBase):
"""Base class of all tvm Expressions"""
- # In Python3, We have to explicity tell interpreter to retain __hash__ if we overide __eq__
+ # In Python3, We have to explicitly tell interpreter to retain __hash__ if we overide __eq__
# https://docs.python.org/3.1/reference/datamodel.html#object.__hash__
__hash__ = NodeBase.__hash__
identity_list=None,
convert_map=None):
"""Convert from Caffe2 operator to Relay operator.
- The converter must specify conversions explicity for incompatible name, and
+ The converter must specify conversions explicitly for incompatible name, and
apply handlers to operator attributes.
Parameters
attrs,
opset):
"""Convert ONNX operator into a Relay operator.
- The converter must specify conversions explicity for incompatible name, and
+ The converter must specify conversions explicitly for incompatible name, and
apply handlers to operator attributes.
Parameters
def _convert_operator(self, op_name, inputs, attrs,
graph, identity_list=None, convert_map=None):
"""Convert from Tensorflow operator to relay operator.
- The converter must specify conversions explicity for incompatible name, and
+ The converter must specify conversions explicitly for incompatible name, and
apply handlers to operator attributes.
Parameters
def test_forward_clip():
data = mx.sym.var('data')
- data = mx.sym.concat(data, -data, dim=1) # negative part explicity
+ data = mx.sym.concat(data, -data, dim=1) # negative part explicitly
mx_sym = mx.sym.clip(data, a_min=0, a_max=1)
verify_mxnet_frontend_impl(mx_sym, (1, 3, 100, 100), (1, 6, 100, 100))