forked from huawei/mindspore2022
52 lines
2.2 KiB
Python
52 lines
2.2 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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"""generate json desc for softmax"""
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from mindspore._extends.graph_kernel.model import model_builder as builder
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def expand_softmax(expand_info):
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"""Softmax expander"""
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# get op info.
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input_desc = expand_info['input_desc'][0]
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attrs = expand_info['attr']
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axis = None
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for item in attrs:
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if 'axis' in item:
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axis = item['axis']
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graph_builder = builder.GraphBuilder()
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# generate a graph.
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with graph_builder.graph_scope('main') as graph_scope:
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# create tensor input.
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input_x = graph_builder.tensor(input_desc['shape'], input_desc['data_type'], input_desc['format'])
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# cal softmax.
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if input_x.dtype == 'float32':
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input_x_cast = graph_builder.emit('Cast', [input_x], attrs={'dst_type': 'float16'})
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max_x = graph_builder.emit('ReduceMax', [input_x_cast], attrs={'reduce_axis': axis, 'keep_dims': True})
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max_x = graph_builder.emit('Cast', [max_x], attrs={'dst_type': 'float32'})
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else:
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max_x = graph_builder.emit('ReduceMax', [input_x], attrs={'reduce_axis': axis, 'keep_dims': True})
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data_sub = graph_builder.emit('Sub', [input_x, max_x])
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data_exp = graph_builder.emit('Exp', [data_sub])
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data_expsum = graph_builder.emit('ReduceSum', [data_exp], attrs={'reduce_axis': axis, 'keep_dims': True})
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result = graph_builder.emit('RealDiv', [data_exp, data_expsum])
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# set graph output.
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graph_scope.set_output(result)
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graph = graph_builder.get()[0]
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return graph
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