You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/10/20 20:42:56 UTC
[GitHub] eric-haibin-lin closed pull request #12810: Add index_copy()
operator
eric-haibin-lin closed pull request #12810: Add index_copy() operator
URL: https://github.com/apache/incubator-mxnet/pull/12810
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git a/src/operator/contrib/index_copy-inl.h b/src/operator/contrib/index_copy-inl.h
new file mode 100644
index 00000000000..b97138a88f9
--- /dev/null
+++ b/src/operator/contrib/index_copy-inl.h
@@ -0,0 +1,173 @@
+/*
+ * 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.
+ */
+
+/*!
+ * \file index_copy-inl.h
+ * \brief implementation of index_copy tensor operation
+ */
+
+#ifndef MXNET_OPERATOR_CONTRIB_INDEX_COPY_INL_H_
+#define MXNET_OPERATOR_CONTRIB_INDEX_COPY_INL_H_
+
+#include <mxnet/operator_util.h>
+#include <vector>
+#include <limits>
+#include <algorithm>
+#include "../elemwise_op_common.h"
+#include "../mshadow_op.h"
+#include "../mxnet_op.h"
+
+namespace mxnet {
+namespace op {
+
+template<int req>
+struct index_copy_forward {
+ template<typename DType, typename IType>
+ MSHADOW_XINLINE static void Map(int i,
+ int dim,
+ IType* index,
+ DType* new_tensor,
+ DType* out_tensor) {
+ DType* out_ptr = out_tensor + static_cast<int>(index[i]) * dim;
+ DType* new_ptr = new_tensor + i * dim;
+ for (int idx = 0; idx < dim; ++idx) {
+ KERNEL_ASSIGN(out_ptr[idx], req, new_ptr[idx]);
+ }
+ }
+};
+
+template<typename xpu>
+void IndexCopyForward(const nnvm::NodeAttrs& attrs,
+ const OpContext& ctx,
+ const std::vector<TBlob>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<TBlob>& outputs) {
+ CHECK_EQ(inputs.size(), 3U);
+ CHECK_EQ(outputs.size(), 1U);
+ CHECK_EQ(req.size(), 1U);
+ mshadow::Stream<xpu> *s = ctx.get_stream<xpu>();
+ const TBlob& out = outputs[0];
+ const TBlob& original_tensor = inputs[0];
+ const TBlob& idx_vector = inputs[1];
+ const TBlob& copied_tensor = inputs[2];
+ int dim = inputs[2].Size() / inputs[1].Size();
+ // copy original tensor to output
+ mxnet_op::copy(s, out, original_tensor);
+ // index copy
+ MSHADOW_TYPE_SWITCH(out.type_flag_, DType, {
+ MSHADOW_TYPE_SWITCH(idx_vector.type_flag_, IType, {
+ MXNET_ASSIGN_REQ_SWITCH(req[0], req_type, {
+ mxnet_op::Kernel<index_copy_forward<req_type>, xpu>::Launch(s,
+ idx_vector.Size(), dim,
+ idx_vector.dptr<IType>(),
+ copied_tensor.dptr<DType>(),
+ out.dptr<DType>());
+ });
+ });
+ });
+}
+
+template<int req>
+struct index_copy_backward {
+ template<typename DType, typename IType>
+ MSHADOW_XINLINE static void Map(int i,
+ int dim,
+ int index_size,
+ DType* out_grad,
+ IType* index,
+ DType* in_grad_1,
+ DType* in_grad_2) {
+ // Copy to in_grad_2
+ for (int p = 0; p < index_size; ++p) {
+ int idx = static_cast<int>(index[p]);
+ if (i >= idx*dim && i < (idx+1)*dim) {
+ int offset = i - idx*dim;
+ KERNEL_ASSIGN(in_grad_2[p*dim+offset], req, out_grad[i]);
+ return;
+ }
+ }
+ // Copy to in_grad_1
+ KERNEL_ASSIGN(in_grad_1[i], req, out_grad[i]);
+ }
+};
+
+template<typename xpu>
+void IndexCopyBackward(const nnvm::NodeAttrs& attrs,
+ const OpContext& ctx,
+ const std::vector<TBlob>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<TBlob>& outputs) {
+ CHECK_EQ(inputs.size(), 4U);
+ CHECK_EQ(outputs.size(), 3U);
+ mshadow::Stream<xpu> *s = ctx.get_stream<xpu>();
+ const TBlob& out_grad = inputs[0];
+ const TBlob& index = inputs[2];
+ const TBlob& in_grad_1 = outputs[0];
+ const TBlob& in_grad_2 = outputs[2];
+ int dim = inputs[3].Size() / inputs[2].Size();
+ int index_size = inputs[2].Size();
+ // index_copy_backward
+ MSHADOW_TYPE_SWITCH(out_grad.type_flag_, DType, {
+ MSHADOW_TYPE_SWITCH(index.type_flag_, IType, {
+ MXNET_ASSIGN_REQ_SWITCH(req[0], req_type, {
+ mxnet_op::Kernel<index_copy_backward<req_type>, xpu>::Launch(s,
+ out_grad.Size(),
+ dim, index_size,
+ out_grad.dptr<DType>(),
+ index.dptr<IType>(),
+ in_grad_1.dptr<DType>(),
+ in_grad_2.dptr<DType>());
+ });
+ });
+ });
+}
+
+inline bool IndexCopyShape(const nnvm::NodeAttrs& attrs,
+ std::vector<TShape> *in_attrs,
+ std::vector<TShape> *out_attrs) {
+ // inputs[0]: original tensor
+ // inputs[1]: index vector
+ // inputs[2]: copied tensor
+ CHECK_EQ(in_attrs->size(), 3U);
+ // outputs[0]: a new tensor
+ CHECK_EQ(out_attrs->size(), 1U);
+ // inputs[1] must be a vector
+ CHECK_EQ(in_attrs->at(1).ndim(), 1);
+ // Shape matching
+ CHECK_EQ(in_attrs->at(0).ndim(), in_attrs->at(2).ndim());
+ for (size_t i = 0; i < in_attrs->at(0).ndim(); ++i) {
+ if (i == 0) {
+ CHECK_GE(in_attrs->at(0)[i], in_attrs->at(2)[i]);
+ } else {
+ CHECK_EQ(in_attrs->at(0)[i], in_attrs->at(2)[i]);
+ }
+ }
+ // The the length of the fitrst dim of copied tensor
+ // must equal to the size of index vector
+ CHECK_EQ(in_attrs->at(1)[0], in_attrs->at(2)[0]);
+ SHAPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0));
+ SHAPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0));
+ return out_attrs->at(0).ndim() != 0U &&
+ out_attrs->at(0).Size() != 0U;
+}
+
+} // namespace op
+} // namespace mxnet
+
+#endif // MXNET_OPERATOR_CONTRIB_INDEX_COPY_INL_H_
diff --git a/src/operator/contrib/index_copy.cc b/src/operator/contrib/index_copy.cc
new file mode 100644
index 00000000000..07067a3f993
--- /dev/null
+++ b/src/operator/contrib/index_copy.cc
@@ -0,0 +1,73 @@
+/*
+ * 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.
+ */
+
+/*!
+ * \file index_copy.cc
+ * \brief
+ */
+#include "./index_copy-inl.h"
+
+namespace mxnet {
+namespace op {
+
+NNVM_REGISTER_OP(_contrib_index_copy)
+.describe(R"code(Copies the elements of a `new_tensor` into the `old_tensor` by
+selecting the indices in the order given in `index`. The output will be a new tensor
+contains the rest elements of old tensor and the copied elements of new tensor.
+For example, if `index[i] == j`, then the `i`th row of `new_tensor` is copied to the
+`j`th row of output.
+
+The `index` must be a vector and it must have the same size with the `0`th dimimention of
+`new_tensor`. Also, the `0`th dimimention of old_tensor must `>=` the `0`th dimimention of
+`new_tensor`, or an error will be raised.
+
+Examples::
+
+x = mx.nd.zeros((5,3))
+t = mx.nd.array([[1,2,3],[4,5,6],[7,8,9]])
+index = mx.nd.array([0,4,2])
+
+mx.nd.contrib.index_copy(x, index, t)
+
+[[1. 2. 3.]
+ [0. 0. 0.]
+ [7. 8. 9.]
+ [0. 0. 0.]
+ [4. 5. 6.]]
+<NDArray 5x3 @cpu(0)>
+
+)code" ADD_FILELINE)
+.set_num_inputs(3)
+.set_num_outputs(1)
+.set_attr<nnvm::FInferShape>("FInferShape", IndexCopyShape)
+.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<3, 1>)
+.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_contrib_backward_index_copy"})
+.set_attr<FCompute>("FCompute<cpu>", IndexCopyForward<cpu>)
+.add_argument("old_tensor", "NDArray-or-Symbol", "Old tensor")
+.add_argument("index_vector", "NDArray-or-Symbol", "Index vector")
+.add_argument("new_tensor", "NDArray-or-Symbol", "New tensor to be copied");
+
+NNVM_REGISTER_OP(_contrib_backward_index_copy)
+.set_num_inputs(4)
+.set_num_outputs(3)
+.set_attr<nnvm::TIsBackward>("TIsBackward", true)
+.set_attr<FCompute>("FCompute<cpu>", IndexCopyBackward<cpu>);
+
+} // namespace op
+} // namespace mxnet
diff --git a/src/operator/contrib/index_copy.cu b/src/operator/contrib/index_copy.cu
new file mode 100644
index 00000000000..dc416114b04
--- /dev/null
+++ b/src/operator/contrib/index_copy.cu
@@ -0,0 +1,36 @@
+/*
+ * 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.
+ */
+
+/*!
+ * \file index_copy.cc
+ * \brief
+ */
+#include "./index_copy-inl.h"
+
+namespace mxnet {
+namespace op {
+
+NNVM_REGISTER_OP(_contrib_index_copy)
+.set_attr<FCompute>("FCompute<gpu>", IndexCopyForward<gpu>);
+
+NNVM_REGISTER_OP(_contrib_backward_index_copy)
+.set_attr<FCompute>("FCompute<gpu>", IndexCopyBackward<gpu>);
+
+} // namespace op
+} // namespace mxnet
diff --git a/tests/python/unittest/test_operator.py b/tests/python/unittest/test_operator.py
index a7f484e81b3..a1eccf761f0 100644
--- a/tests/python/unittest/test_operator.py
+++ b/tests/python/unittest/test_operator.py
@@ -4639,6 +4639,29 @@ def test_quantization_op():
assert same(qa.asnumpy(), qa_real.asnumpy())
assert same(a_.asnumpy(), a_real.asnumpy())
+@with_seed()
+def test_index_copy():
+ x = mx.nd.zeros((5,3))
+ t = mx.nd.array([[1,2,3],[4,5,6],[7,8,9]])
+ index = mx.nd.array([0,4,2])
+
+ x.attach_grad()
+ t.attach_grad()
+ index.attach_grad()
+
+ with mx.autograd.record():
+ out = mx.nd.contrib.index_copy(x, index, t)
+ out.backward()
+
+ tensor = mx.nd.array([[1,2,3],[0,0,0],[7,8,9],[0,0,0],[4,5,6]])
+ x_grad = mx.nd.array([[0,0,0],[1,1,1],[0,0,0],[1,1,1],[0,0,0]])
+ t_grad = mx.nd.array([[1,1,1],[1,1,1],[1,1,1]])
+ index_grad = mx.nd.array([0,0,0])
+
+ assert same(out.asnumpy(), tensor.asnumpy())
+ assert same(x.grad.asnumpy(), x_grad.asnumpy())
+ assert same(t.grad.asnumpy(), t_grad.asnumpy())
+ assert same(index.grad.asnumpy(), index_grad.asnumpy())
@with_seed()
def test_div_sqrt_dim():
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services