chore: import upstream snapshot with attribution

2026-07-13 13:36:25 +08:00
commit 26446540fa
3151 changed files with 974126 additions and 0 deletions
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+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+# pylint: disable=invalid-name
+"""OneHot in python"""
+
+import numpy as np
+
+
+def one_hot(indices, on_value, off_value, depth, axis, dtype):
+    """one_hot operator implemented in numpy.
+
+    Returns a one-hot tensor where the locations repsented by indices take value on_value,
+    other locations take value off_value.
+    Final dimension is <indices outer dimensions> x depth x <indices inner dimensions>.
+
+    Parameters
+    ----------
+    indices : numpy.ndarray
+        Locations to set to on_value.
+
+    on_value : int/float
+        Value to fill at indices.
+
+    off_value : int/float
+        Value to fill at all other positions besides indices.
+
+    depth : int
+        Depth of the one-hot dimension.
+
+    axis : int
+        Axis to fill.
+
+    dtype : str
+        Data type of the output tensor.
+
+    Returns
+    -------
+    ret : tvm.te.Tensor
+        The one-hot tensor.
+    """
+    oshape = []
+    true_axis = len(indices.shape) if axis == -1 else axis
+    ndim = len(indices.shape) + 1
+    indices_index = 0
+    for i in range(0, ndim):
+        if i == true_axis:
+            oshape.append(depth)
+        else:
+            oshape.append(indices.shape[indices_index])
+            indices_index += 1
+
+    out = np.empty(oshape)
+    output_indices = list(np.ndindex(out.shape))
+    for output_index in output_indices:
+        indices_indices = []
+        for i, out_idx in enumerate(output_index):
+            if i == true_axis:
+                continue
+            indices_indices.append(out_idx)
+
+        index = output_index[true_axis]
+        if indices[tuple(indices_indices)] == index:
+            out[output_index] = on_value
+        else:
+            out[output_index] = off_value
+
+    return out.astype(dtype)