2bf8d910f6
* [Docs][PyOV] update python snippets * first snippet * Fix samples debug * Fix linter * part1 * Fix speech sample * update model state snippet * add serialize * add temp dir * CPU snippets update (#134) * snippets CPU 1/6 * snippets CPU 2/6 * snippets CPU 3/6 * snippets CPU 4/6 * snippets CPU 5/6 * snippets CPU 6/6 * make module TODO: REMEMBER ABOUT EXPORTING PYTONPATH ON CIs ETC * Add static model creation in snippets for CPU * export_comp_model done * leftovers * apply comments * apply comments -- properties * small fixes * rempve debug info * return IENetwork instead of Function * apply comments * revert precision change in common snippets * update opset * [PyOV] Edit docs for the rest of plugins (#136) * modify main.py * GNA snippets * GPU snippets * AUTO snippets * MULTI snippets * HETERO snippets * Added properties * update gna * more samples * Update docs/OV_Runtime_UG/model_state_intro.md * Update docs/OV_Runtime_UG/model_state_intro.md * attempt1 fix ci * new approach to test * temporary remove some files from run * revert cmake changes * fix ci * fix snippet * fix py_exclusive snippet * fix preprocessing snippet * clean-up main * remove numpy installation in gha * check for GPU * add logger * iexclude main * main update * temp * Temp2 * Temp2 * temp * Revert temp * add property execution devices * hide output from samples --------- Co-authored-by: p-wysocki <przemyslaw.wysocki@intel.com> Co-authored-by: Jan Iwaszkiewicz <jan.iwaszkiewicz@intel.com> Co-authored-by: Karol Blaszczak <karol.blaszczak@intel.com>
40 lines
916 B
Python
40 lines
916 B
Python
# Copyright (C) 2022 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import openvino as ov
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from snippets import get_model
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def main():
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model = get_model()
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core = ov.Core()
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if "GPU" not in core.available_devices:
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return 0
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#! [dynamic_batch]
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core = ov.Core()
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C = 3
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H = 224
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W = 224
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model.reshape([(1, 10), C, H, W])
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# compile model and create infer request
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compiled_model = core.compile_model(model, "GPU")
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infer_request = compiled_model.create_infer_request()
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# create input tensor with specific batch size
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input_tensor = ov.Tensor(model.input().element_type, [2, C, H, W])
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# ...
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results = infer_request.infer([input_tensor])
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#! [dynamic_batch]
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assert list(results.keys())[0].partial_shape == ov.PartialShape([(1, 10), 3, 224, 224])
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assert list(results.values())[0].shape == tuple(ov.Shape([2, 3, 224, 224]))
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