110 lines
3.9 KiB
Python
110 lines
3.9 KiB
Python
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# Copyright (C) 2018-2025 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import sys
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import numpy as np
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from openvino import Shape, PartialShape, Dimension # pylint: disable=no-name-in-module,import-error
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from openvino.tools.ovc.error import Error
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def get_static_shape(shape: [PartialShape, list, tuple], dynamic_value=None):
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# Current function returns list with static dimensions with following logic.
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# For dynamic dimensions return lower boundaries if they are set, otherwise
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# return upper boundaries if they are set. If dimension is fully dynamic then raise error.
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shape_list = []
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for idx, dim in enumerate(shape):
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if isinstance(dim, int):
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if dim == -1:
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shape_list.append(dynamic_value)
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continue
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shape_list.append(dim)
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elif isinstance(dim, np.int64):
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if dim == np.int64(-1):
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shape_list.append(dynamic_value)
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continue
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shape_list.append(dim)
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elif isinstance(dim, tuple):
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# tuple where (min_length, max_length), the format which uses MO cli parser
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assert len(dim) == 2, "Unknown dimension type {}".format(dim)
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if dim[0] > 0:
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shape_list.append(dim[0])
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elif dim[1] < np.iinfo(np.int64).max:
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shape_list.append(dim[1])
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else:
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shape_list.append(dynamic_value)
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continue
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elif isinstance(dim, Dimension):
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if dim.is_static or dim.get_min_length() > 0:
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shape_list.append(dim.get_min_length())
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elif dim.get_max_length() != -1:
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shape_list.append(dim.get_max_length())
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else:
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shape_list.append(dynamic_value)
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continue
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else:
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raise Error("Unknown dimension type {}".format(dim))
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return tuple(shape_list)
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def get_dynamic_dims(shape: [PartialShape, list, tuple]):
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dynamic_dims = []
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for idx, dim in enumerate(shape):
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if isinstance(dim, int):
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if dim == -1:
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dynamic_dims.append(idx)
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if isinstance(dim, np.int64):
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if dim == np.int64(-1):
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dynamic_dims.append(idx)
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elif isinstance(dim, tuple):
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dynamic_dims.append(idx)
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elif isinstance(dim, Dimension):
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if dim.get_min_length() == 0 and dim.get_max_length() == -1:
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dynamic_dims.append(idx)
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return dynamic_dims
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def tensor_to_int_list(tensor):
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assert hasattr(tensor, 'numpy'), "Could not get value of provided tensor: {}".format(tensor)
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tensor_numpy = tensor.numpy()
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assert tensor_numpy.dtype == np.int32, "Unexpected type of provided tensor. Expected int32, got: {}".format(
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tensor_numpy.dtype)
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return tensor_numpy.tolist()
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def to_partial_shape(shape):
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if 'tensorflow' in sys.modules:
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import tensorflow as tf # pylint: disable=import-error
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if isinstance(shape, tf.Tensor):
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return PartialShape(tensor_to_int_list(shape))
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if isinstance(shape, tf.TensorShape):
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return PartialShape(list(shape))
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if 'paddle' in sys.modules:
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import paddle
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if isinstance(shape, paddle.Tensor):
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return PartialShape(tensor_to_int_list(shape))
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return PartialShape(shape)
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def is_shape_type(value):
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if isinstance(value, PartialShape):
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return True
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if 'tensorflow' in sys.modules:
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import tensorflow as tf # pylint: disable=import-error
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if isinstance(value, (tf.TensorShape, tf.Tensor)):
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return True
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if 'paddle' in sys.modules:
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import paddle
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if isinstance(value, paddle.Tensor):
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return True
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if isinstance(value, Shape):
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return True
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if isinstance(value, list) or isinstance(value, tuple):
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for dim in value:
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if not (isinstance(dim, Dimension) or isinstance(dim, int)):
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return False
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return True
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return False
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