[GitHub] sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module to import onnx models into mxnet
sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module
to import onnx models into mxnet
URL: https://github.com/apache/incubator-mxnet/pull/9963#discussion_r172272632
##
File path: python/mxnet/contrib/onnx/_import/import_onnx.py
##
@@ -0,0 +1,166 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you 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.
+
+# coding: utf-8
+# pylint: disable=invalid-name,too-many-locals,no-self-use
+""" Support import export formats."""
+from __future__ import absolute_import as _abs
+from import symbol
+from import ndarray as nd
+from .import_helper import _convert_map, _pad_sequence_fix
+
+def _convert_operator(op_name, attrs, inputs, convert_map=None):
+"""Convert from onnx operator to mxnet operator.
+The converter must specify conversions explicitly for incompatible name,
and
+apply handlers to operator attributes.
+
+Parameters
+--
+op_name : str
+Operator name, such as Convolution, FullyConnected
+attrs : dict
+Dict of operator attributes
+inputs: list
+list of inputs to the operator
+convert_map : dict
+Dict of name : callable, where name is the op's name that
+require conversion to mxnet, callable are functions which
+take attrs and return (new_op_name, new_attrs, inputs)
+
+Returns
+---
+(op_name, attrs)
+Converted (op_name, attrs) for mxnet.
+"""
+convert_map = convert_map if convert_map else _convert_map
+if op_name in convert_map:
+op_name, attrs, inputs = convert_map[op_name](op_name, attrs, inputs)
+else:
+raise NotImplementedError("Operator {} not
implemented.".format(op_name))
+op = getattr(symbol, op_name, None)
+if not op:
+raise RuntimeError("Unable to map op_name {} to sym".format(op_name))
+return op, attrs, inputs
+
+class GraphProto(object): # pylint: disable=too-few-public-methods
+"""A helper class for handling mxnet symbol copying from pb2.GraphProto.
+Definition: https://github.com/onnx/onnx/blob/master/onnx/onnx.proto
+"""
+def __init__(self):
+self._nodes = {}
+self._params = {}
+self._renames = {}
+self._num_input = 0
+self._num_param = 0
+
+def from_onnx(self, graph):
+"""Construct symbol from onnx graph.
+The inputs from onnx graph is vague, only providing "1", "2"...
+For convenience, we rename the `real` input names to "input_0",
+"input_1"... And renaming parameters to "param_0", "param_1"...
+
+Parameters
+--
+graph : onnx protobuf object
+The loaded onnx graph
+
+Returns
+---
+sym :symbol.Symbol
+The returned mxnet symbol
+params : dict
+A dict of name: nd.array pairs, used as pretrained weights
+"""
+# parse network inputs, aka parameters
+for init_tensor in graph.initializer:
+if not init_tensor.name.strip():
+raise ValueError("Tensor's name is required.")
+self._params[init_tensor.name] = self._parse_array(init_tensor)
+
+# converting GraphProto message
+for i in graph.input:
+if i.name in self._params:
+# i is a param instead of input
+name_param = 'param_{}'.format(self._num_param)
+self._num_param += 1
+self._params[name_param] = self._params.pop(i.name)
+self._nodes[name_param] = symbol.Variable(name=name_param,
+
shape=self._params[name_param].shape)
+self._renames[i.name] = name_param
+else:
+name_input = 'input_{}'.format(self._num_input)
+self._num_input += 1
+self._nodes[name_input] = symbol.Variable(name=name_input)
+self._renames[i.name] = name_input
+
+# constructing nodes, nodes are stored as directed acyclic graph
+# converting NodeProto message
+for node in graph.node:
+op_name = node.op_type
+node_name = node.name.strip()
+node_name =
[GitHub] sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module to import onnx models into mxnet
sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module
to import onnx models into mxnet
URL: https://github.com/apache/incubator-mxnet/pull/9963#discussion_r172272317
##
File path: python/mxnet/contrib/onnx/_import/import_onnx.py
##
@@ -0,0 +1,166 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you 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.
+
+# coding: utf-8
+# pylint: disable=invalid-name,too-many-locals,no-self-use
+""" Support import export formats."""
+from __future__ import absolute_import as _abs
+from import symbol
+from import ndarray as nd
+from .import_helper import _convert_map, _pad_sequence_fix
+
+def _convert_operator(op_name, attrs, inputs, convert_map=None):
+"""Convert from onnx operator to mxnet operator.
+The converter must specify conversions explicitly for incompatible name,
and
+apply handlers to operator attributes.
+
+Parameters
+--
+op_name : str
+Operator name, such as Convolution, FullyConnected
+attrs : dict
+Dict of operator attributes
+inputs: list
+list of inputs to the operator
+convert_map : dict
+Dict of name : callable, where name is the op's name that
+require conversion to mxnet, callable are functions which
+take attrs and return (new_op_name, new_attrs, inputs)
+
+Returns
+---
+(op_name, attrs)
+Converted (op_name, attrs) for mxnet.
+"""
+convert_map = convert_map if convert_map else _convert_map
+if op_name in convert_map:
+op_name, attrs, inputs = convert_map[op_name](op_name, attrs, inputs)
+else:
+raise NotImplementedError("Operator {} not
implemented.".format(op_name))
+op = getattr(symbol, op_name, None)
+if not op:
+raise RuntimeError("Unable to map op_name {} to sym".format(op_name))
+return op, attrs, inputs
+
+class GraphProto(object): # pylint: disable=too-few-public-methods
+"""A helper class for handling mxnet symbol copying from pb2.GraphProto.
+Definition: https://github.com/onnx/onnx/blob/master/onnx/onnx.proto
+"""
+def __init__(self):
+self._nodes = {}
+self._params = {}
+self._renames = {}
+self._num_input = 0
+self._num_param = 0
+
+def from_onnx(self, graph):
+"""Construct symbol from onnx graph.
+The inputs from onnx graph is vague, only providing "1", "2"...
+For convenience, we rename the `real` input names to "input_0",
+"input_1"... And renaming parameters to "param_0", "param_1"...
+
+Parameters
+--
+graph : onnx protobuf object
+The loaded onnx graph
+
+Returns
+---
+sym :symbol.Symbol
+The returned mxnet symbol
+params : dict
+A dict of name: nd.array pairs, used as pretrained weights
+"""
+# parse network inputs, aka parameters
+for init_tensor in graph.initializer:
+if not init_tensor.name.strip():
+raise ValueError("Tensor's name is required.")
+self._params[init_tensor.name] = self._parse_array(init_tensor)
+
+# converting GraphProto message
+for i in graph.input:
+if i.name in self._params:
+# i is a param instead of input
+name_param = 'param_{}'.format(self._num_param)
+self._num_param += 1
+self._params[name_param] = self._params.pop(i.name)
+self._nodes[name_param] = symbol.Variable(name=name_param,
+
shape=self._params[name_param].shape)
+self._renames[i.name] = name_param
+else:
+name_input = 'input_{}'.format(self._num_input)
+self._num_input += 1
+self._nodes[name_input] = symbol.Variable(name=name_input)
+self._renames[i.name] = name_input
+
+# constructing nodes, nodes are stored as directed acyclic graph
+# converting NodeProto message
+for node in graph.node:
+op_name = node.op_type
+node_name = node.name.strip()
+node_name =
[GitHub] sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module to import onnx models into mxnet
sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module
to import onnx models into mxnet
URL: https://github.com/apache/incubator-mxnet/pull/9963#discussion_r172270960
##
File path: python/mxnet/contrib/onnx/_import/import_onnx.py
##
@@ -0,0 +1,166 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you 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.
+
+# coding: utf-8
+# pylint: disable=invalid-name,too-many-locals,no-self-use
+""" Support import export formats."""
+from __future__ import absolute_import as _abs
+from import symbol
+from import ndarray as nd
+from .import_helper import _convert_map, _pad_sequence_fix
+
+def _convert_operator(op_name, attrs, inputs, convert_map=None):
+"""Convert from onnx operator to mxnet operator.
+The converter must specify conversions explicitly for incompatible name,
and
+apply handlers to operator attributes.
+
+Parameters
+--
+op_name : str
+Operator name, such as Convolution, FullyConnected
+attrs : dict
+Dict of operator attributes
+inputs: list
+list of inputs to the operator
+convert_map : dict
+Dict of name : callable, where name is the op's name that
+require conversion to mxnet, callable are functions which
+take attrs and return (new_op_name, new_attrs, inputs)
+
+Returns
+---
+(op_name, attrs)
+Converted (op_name, attrs) for mxnet.
+"""
+convert_map = convert_map if convert_map else _convert_map
+if op_name in convert_map:
+op_name, attrs, inputs = convert_map[op_name](op_name, attrs, inputs)
+else:
+raise NotImplementedError("Operator {} not
implemented.".format(op_name))
+op = getattr(symbol, op_name, None)
+if not op:
+raise RuntimeError("Unable to map op_name {} to sym".format(op_name))
+return op, attrs, inputs
+
+class GraphProto(object): # pylint: disable=too-few-public-methods
+"""A helper class for handling mxnet symbol copying from pb2.GraphProto.
+Definition: https://github.com/onnx/onnx/blob/master/onnx/onnx.proto
+"""
+def __init__(self):
+self._nodes = {}
+self._params = {}
+self._renames = {}
+self._num_input = 0
+self._num_param = 0
+
+def from_onnx(self, graph):
+"""Construct symbol from onnx graph.
+The inputs from onnx graph is vague, only providing "1", "2"...
+For convenience, we rename the `real` input names to "input_0",
+"input_1"... And renaming parameters to "param_0", "param_1"...
+
+Parameters
+--
+graph : onnx protobuf object
+The loaded onnx graph
+
+Returns
+---
+sym :symbol.Symbol
+The returned mxnet symbol
+params : dict
+A dict of name: nd.array pairs, used as pretrained weights
+"""
+# parse network inputs, aka parameters
+for init_tensor in graph.initializer:
+if not init_tensor.name.strip():
+raise ValueError("Tensor's name is required.")
+self._params[init_tensor.name] = self._parse_array(init_tensor)
+
+# converting GraphProto message
+for i in graph.input:
+if i.name in self._params:
+# i is a param instead of input
+name_param = 'param_{}'.format(self._num_param)
+self._num_param += 1
+self._params[name_param] = self._params.pop(i.name)
+self._nodes[name_param] = symbol.Variable(name=name_param,
Review comment:
Do we have dtype information? If yes, it would be good idea to use dtype as
well than assuming fp32 default. Helps in fp16 and other type support later.
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
With regards,
Apache Git Services
[GitHub] sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module to import onnx models into mxnet
sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module to import onnx models into mxnet URL: https://github.com/apache/incubator-mxnet/pull/9963#discussion_r172269243 ## File path: python/mxnet/contrib/onnx/_import/import_helper.py ## @@ -0,0 +1,29 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +# coding: utf-8 +# pylint: disable=invalid-name +"""Operator attributes conversion""" +from . import * Review comment: nit: Instead of * , can we explicitly list all imported modules This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module to import onnx models into mxnet
sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module
to import onnx models into mxnet
URL: https://github.com/apache/incubator-mxnet/pull/9963#discussion_r172298550
##
File path: python/mxnet/contrib/onnx/_import/op_translations/reduce_max.py
##
@@ -0,0 +1,23 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you 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.
+
+# coding: utf-8
+from ..translation_utils import _fix_attribute_names
+
+def reduce_max(op_name, attrs, inputs):
+new_attr = _fix_attrbute_names(attrs, {'axes':'axis'})
+return 'max', attrs, inputs
Review comment:
nit: new line
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
With regards,
Apache Git Services
[GitHub] sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module to import onnx models into mxnet
sandeep-krishnamurthy commented on a change in pull request #9963: Onnx Module
to import onnx models into mxnet
URL: https://github.com/apache/incubator-mxnet/pull/9963#discussion_r172293282
##
File path: python/mxnet/contrib/onnx/_import/translation_utils/__init__.py
##
@@ -0,0 +1,141 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you 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.
+
+# coding: utf-8
+# pylint:
disable=invalid-name,no-self-use,too-many-branches,too-few-public-methods,too-many-arguments
+from __future__ import absolute_import as _abs
+from base import string_types
+
+def _fix_attribute_names(attrs, change_map):
+new_attr = {}
+for k in attrs.keys():
+if k in change_map:
+new_attr[change_map[k]] = attrs[k]
+else:
+new_attr[k] = attrs[k]
+return new_attr
+
+def _fix_pooling(op_name, inputs, new_attr):
+"""onnx pooling operator supports asymmetrical padding
+Adding pad operator before pooling in mxnet to work with onnx"""
+pool_type = 'avg' if op_name == 'AveragePool' else 'max'
+stride = new_attr.get('strides')
+kernel = new_attr.get('kernel_shape')
+padding = new_attr.get('pads')
+pad_width = (0, 0, 0, 0) + _pad_sequence_fix(padding, len(kernel))
+new_pad_op = symbol.pad(inputs[0], mode='constant', pad_width=pad_width)
+new_pooling_op = symbol.Pooling(new_pad_op, pool_type=pool_type,
+stride=stride, kernel=kernel)
+return new_pooling_op
+
+def _fix_slice(inputs, new_attr):
+"""onnx slice provides slicing on multiple axis. Adding multiple
slice_axis operator
+for multiple axes from mxnet"""
+begin = new_attr.get('begin')
+end = new_attr.get('end')
+axes = new_attr.get('axis', tuple(range(len(begin
+slice_op = symbol.slice_axis(inputs[0], axis=axes[0], begin=begin[0],
end=end[0])
+if len(axes) > 1:
+for i, axis in enumerate(axes):
+slice_op = symbol.slice_axis(slice_op, axis=axis, begin=begin[i],
end=end[i])
+return slice_op
+
+def _fix_squeeze(inputs, new_attr):
+"""
+MXNet doesnt have a squeeze operator.
+Using "split" to perform similar operation.
+"split" can be slower compared to "reshape".
+ This can have performance impact.
+ TODO: Remove this implementation once mxnet adds the support.
Review comment:
Related GitHub issue link?
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
With regards,
Apache Git Services
