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//***************************************************************************** | ||
// Copyright 2017-2021 Intel Corporation | ||
// | ||
// Licensed 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. | ||
//***************************************************************************** | ||
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#include <ngraph/opsets/opset6.hpp> | ||
#include "shape.hpp" | ||
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namespace ngraph { | ||
namespace frontend { | ||
namespace pdpd { | ||
namespace op { | ||
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NamedOutputs shape (const NodeContext& node) { | ||
auto data = node.get_ng_input("Input"); | ||
return node.default_single_output_mapping({std::make_shared<ngraph::opset6::ShapeOf>(data)}, {"Out"}); | ||
} | ||
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}}}} |
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//***************************************************************************** | ||
// Copyright 2017-2021 Intel Corporation | ||
// | ||
// Licensed 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. | ||
//***************************************************************************** | ||
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#pragma once | ||
#include "node_context.hpp" | ||
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namespace ngraph { | ||
namespace frontend { | ||
namespace pdpd { | ||
namespace op { | ||
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NamedOutputs shape (const NodeContext& node); | ||
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}}}} |
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37 changes: 37 additions & 0 deletions
37
ngraph/test/files/paddlepaddle/gen_scripts/generate_shape.py
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# | ||
# pool2d paddle model generator | ||
# | ||
import numpy as np | ||
from save_model import saveModel | ||
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data_type = 'float32' | ||
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def pdpd_shape(name : str, x): | ||
import paddle as pdpd | ||
pdpd.enable_static() | ||
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with pdpd.static.program_guard(pdpd.static.Program(), pdpd.static.Program()): | ||
node_x = pdpd.static.data(name='x', shape=x.shape, dtype='float32') | ||
out = pdpd.shape(node_x) | ||
out = pdpd.cast(out, np.float32) | ||
cpu = pdpd.static.cpu_places(1) | ||
exe = pdpd.static.Executor(cpu[0]) | ||
# startup program will call initializer to initialize the parameters. | ||
exe.run(pdpd.static.default_startup_program()) | ||
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outs = exe.run( | ||
feed={'x': x}, | ||
fetch_list=[out]) | ||
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saveModel(name, exe, feedkeys=['x'], fetchlist=[out], inputs=[x], outputs=[outs[0]]) | ||
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return outs[0] | ||
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def main(): | ||
p=0.5 | ||
data = np.random.random(size=(2,3)).astype('float32') | ||
pdpd_shape("shape", data) | ||
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if __name__ == "__main__": | ||
main() |
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transpose2, | ||
unsqueeze, | ||
yolo_box_test1, | ||
shape, |
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