Anton Chetverikov
6b54e738d7
* Allign attribute values in spec * Fix wrong attribute name in spec * Add `get_boolean_attr` function * Add get_type function * Update conv attrs * Update copyright year * Add missed attrs, update copyright year * Fix year in copyright * Update ir parser for RegionYolo layer * Remove wrong changes for BinaryConvolution * Remove get_type function as it no more needed * Update check for reduce ops * Fix error in reduce attrs * Update ir_engine to work with bool attrs * Update DetectionOutput operation * Update PSROIPooling * remove redundant attrs from spec * Update get_boolean_attr function * Update Reduce operations * Update DetectionOutput specification * Update specification for missed attrs * Apply comments * Fixconst renumbering logic * Fix typo * Change default value to fix broken shape inference * Add additional asserts * Add comment * model-optimizer/mo/utils/ir_reader/layer_to_class.py * Sort imports * Sort imports * Update year in copyright * Update const * Remove changes from const restoring * Rename function * remove unnecessary changes * model-optimizer/mo/front/extractor_test.py * Fix year in copyright * Add soft_get * Fix exclude-pad attribute name for AvgPool operation * Update exclude_pad attribute values * Remove useless comment * Update examples in specification * Remove file added by mistake * Resolve comments * Resolve comments * Add return value * Allign global_pool attribute
89 lines
2.9 KiB
Python
89 lines
2.9 KiB
Python
"""
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Copyright (C) 2018-2021 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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from mo.front.common.partial_infer.utils import mark_input_bins
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from mo.front.extractor import bool_to_str
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from mo.graph.graph import Node, Graph
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from mo.ops.op import Op
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from mo.utils.error import Error
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class GRUCell(Op):
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""" A single GRU cell (without a loop).
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2 inputs:
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- [0, required] input data (2D),
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- [1, required] initial hidden state (2D),
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2 blobs:
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- [2, required] cell FC weights
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- [3, required] cell FC biases
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1 outputs:
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- [required] output data / resulting hidden state (2D)
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"""
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op = 'GRUCell'
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def __init__(self, graph: Graph, attrs: dict):
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mandatory_props = {
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'type': __class__.op,
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'op': __class__.op,
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'infer': __class__.infer,
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'in_ports_count': 4,
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'out_ports_count': 1,
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'version': 'opset3',
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'wr_input_id': 2,
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'gates_count': 3,
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'linear_before_reset': False,
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}
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super().__init__(graph, mandatory_props, attrs)
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def supported_attrs(self):
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return [
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'hidden_size', # number of the elements in hidden cell size
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'activations',
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'activation_alpha',
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'activation_beta',
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'clip',
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'linear_before_reset',
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]
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def backend_attrs(self):
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return [
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'hidden_size', # number of the elements in hidden cell size
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('activations', lambda node: ','.join(node.activations) if node.activations is not None else None),
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'activation_alpha',
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'activation_beta',
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'clip',
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('linear_before_reset', lambda node: bool_to_str(node, 'linear_before_reset')),
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]
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@staticmethod
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def infer(node: Node):
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assert len(node.out_nodes()) in [1, 2]
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hidden_shape = node.in_node(1).shape.copy()
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mark_input_bins(node, start_port=2)
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node.out_node(0).shape = hidden_shape
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hidden_size = hidden_shape[1]
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if node.has_valid('hidden_size'):
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if node.hidden_size != hidden_size:
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raise Error("Input shape {} for hidden size doesn't match pre-defined hidden_size in node {}".format(
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node.in_node(1).shape, node.soft_get('name')))
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else:
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node['hidden_size'] = hidden_size
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