wehub-resource-sync
82 lines
2.5 KiB
Python
82 lines
2.5 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. 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,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# pylint: disable=invalid-name
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"""OneHot in python"""
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import numpy as np
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def one_hot(indices, on_value, off_value, depth, axis, dtype):
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"""one_hot operator implemented in numpy.
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Returns a one-hot tensor where the locations repsented by indices take value on_value,
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other locations take value off_value.
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Final dimension is <indices outer dimensions> x depth x <indices inner dimensions>.
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Parameters
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----------
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indices : numpy.ndarray
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Locations to set to on_value.
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on_value : int/float
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Value to fill at indices.
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off_value : int/float
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Value to fill at all other positions besides indices.
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depth : int
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Depth of the one-hot dimension.
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axis : int
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Axis to fill.
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dtype : str
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Data type of the output tensor.
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Returns
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-------
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ret : tvm.te.Tensor
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The one-hot tensor.
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"""
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oshape = []
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true_axis = len(indices.shape) if axis == -1 else axis
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ndim = len(indices.shape) + 1
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indices_index = 0
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for i in range(0, ndim):
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if i == true_axis:
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oshape.append(depth)
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else:
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oshape.append(indices.shape[indices_index])
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indices_index += 1
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out = np.empty(oshape)
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output_indices = list(np.ndindex(out.shape))
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for output_index in output_indices:
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indices_indices = []
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for i, out_idx in enumerate(output_index):
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if i == true_axis:
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continue
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indices_indices.append(out_idx)
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index = output_index[true_axis]
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if indices[tuple(indices_indices)] == index:
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out[output_index] = on_value
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else:
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out[output_index] = off_value
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return out.astype(dtype)
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