chore: import upstream snapshot with attribution

python/tvm/topi/nn/space_to_batch_nd.py

@@ -0,0 +1,52 @@
+# 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
+"""TVM operator space_to_batch_nd compute."""
+
+from . import cpp
+
+
+def space_to_batch_nd(data, block_shape, pad_before, pad_after, pad_value=0.0):
+    """Perform batch to space transformation on the data
+
+    Parameters
+    ----------
+    data : tvm.te.Tensor
+        N-D Tensor with shape [batch, spatial_shape, remaining_shapes],
+        where spatial_shape has M dimensions.
+
+    block_shape : list of ints
+        list of size [M] where M is number of spatial dims, specifies block
+        size for each spatial dimension.
+
+    pad_before : list of ints
+        list of shape [M] where M is number of spatial dims, specifies
+        zero-padding size before each spatial dimension.
+
+    pad_after : list of ints
+        list of shape [M] where M is number of spatial dims, specifies
+        zero-padding size after each spatial dimension.
+
+    pad_value : float, optional
+        The value used for padding.
+
+    Returns
+    -------
+    output : tvm.te.Tensor
+    """
+
+    return cpp.nn.space_to_batch_nd(data, block_shape, pad_before, pad_after, pad_value)