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boolean_mask_assign operator for future boolean indexing
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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. | ||
*/ | ||
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/*! | ||
* \file np_boolean_assign.cc | ||
* \brief CPU implementation of Boolean Mask Assign | ||
*/ | ||
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#include "../contrib/boolean_mask-inl.h" | ||
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namespace mxnet { | ||
namespace op { | ||
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template<bool scalar = false> | ||
struct BooleanAssignCPUKernel { | ||
private: | ||
static size_t bin_search(const size_t* idx, | ||
const size_t idx_size, | ||
const size_t i) { | ||
size_t left = 0, right = idx_size, mid = (left + right) / 2; | ||
while (left != right) { | ||
if (idx[mid] == i + 1) { | ||
if (idx[mid - 1] == i) { | ||
mid -= 1; | ||
break; | ||
} else if (idx[mid - 1] == i + 1) { | ||
right = mid; | ||
mid = (left + right) / 2; | ||
} | ||
} else if (idx[mid] == i) { | ||
if (idx[mid + 1] == i + 1) { | ||
break; | ||
} else { | ||
left = mid; | ||
mid = (left + right + 1) / 2; | ||
} | ||
} else if (idx[mid] < i + 1) { | ||
left = mid; | ||
mid = (left + right + 1) / 2; | ||
} else if (idx[mid] > i + 1) { | ||
right = mid; | ||
mid = (left + right) / 2; | ||
} | ||
} | ||
return mid; | ||
} | ||
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public: | ||
template<typename DType> | ||
static void Map(int i, | ||
DType* data, | ||
const size_t* idx, | ||
const size_t idx_size, | ||
const size_t leading, | ||
const size_t middle, | ||
const size_t trailing, | ||
const DType val) { | ||
// binary search for the turning point | ||
size_t mid = bin_search(idx, idx_size, i); | ||
// final answer is in mid | ||
for (size_t l = 0; l < leading; ++l) { | ||
for (size_t t = 0; t < trailing; ++t) { | ||
data[(l * middle + mid) * trailing + t] = val; | ||
} | ||
} | ||
} | ||
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template<typename DType> | ||
static void Map(int i, | ||
DType* data, | ||
const size_t* idx, | ||
const size_t idx_size, | ||
const size_t leading, | ||
const size_t middle, | ||
const size_t trailing, | ||
DType* tensor) { | ||
// binary search for the turning point | ||
size_t mid = bin_search(idx, idx_size, i); | ||
// final answer is in mid | ||
for (size_t l = 0; l < leading; ++l) { | ||
for (size_t t = 0; t < trailing; ++t) { | ||
data[(l * middle + mid) * trailing + t] = (scalar) ? tensor[0] : tensor[i]; | ||
} | ||
} | ||
} | ||
}; | ||
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bool BooleanAssignShape(const nnvm::NodeAttrs& attrs, | ||
mxnet::ShapeVector *in_attrs, | ||
mxnet::ShapeVector *out_attrs) { | ||
CHECK(in_attrs->size() == 2U || in_attrs->size() == 3U); | ||
CHECK_EQ(out_attrs->size(), 1U); | ||
const TShape& dshape = in_attrs->at(0); | ||
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// mask should have the same shape as the input | ||
SHAPE_ASSIGN_CHECK(*in_attrs, 1, dshape); | ||
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// check if output shape is the same as the input data | ||
SHAPE_ASSIGN_CHECK(*out_attrs, 0, dshape); | ||
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// for tensor version, the tensor should have less than 1 dimension | ||
if (in_attrs->size() == 3U) { | ||
CHECK_LE(in_attrs->at(2).ndim(), 1U) | ||
<< "boolean array indexing assignment requires a 0 or 1-dimensional input, input has " | ||
<< in_attrs->at(2).ndim() <<" dimensions"; | ||
} | ||
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return shape_is_known(out_attrs->at(0)); | ||
} | ||
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bool BooleanAssignType(const nnvm::NodeAttrs& attrs, | ||
std::vector<int> *in_attrs, | ||
std::vector<int> *out_attrs) { | ||
CHECK(in_attrs->size() == 2U || in_attrs->size() == 3U); | ||
CHECK_EQ(out_attrs->size(), 1U); | ||
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// input and output should always have the same type | ||
TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0)); | ||
TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0)); | ||
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if (in_attrs->size() == 3U) { | ||
// if tensor version, the tensor should also have the same type as input | ||
TYPE_ASSIGN_CHECK(*in_attrs, 2, in_attrs->at(0)); | ||
TYPE_ASSIGN_CHECK(*in_attrs, 0, in_attrs->at(2)); | ||
CHECK_NE(in_attrs->at(2), -1); | ||
} | ||
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return out_attrs->at(0) != -1 && in_attrs->at(0) != -1 && in_attrs->at(1) != -1; | ||
} | ||
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// calculate the number of valid (masked) values, also completing the prefix_sum vector | ||
template<typename DType> | ||
size_t GetValidNumCPU(const DType* idx, size_t* prefix_sum, const size_t idx_size) { | ||
prefix_sum[0] = 0; | ||
for (size_t i = 0; i < idx_size; i++) { | ||
prefix_sum[i + 1] = prefix_sum[i] + ((idx[i]) ? 1 : 0); | ||
} | ||
return prefix_sum[idx_size]; | ||
} | ||
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void NumpyBooleanAssignForwardCPU(const nnvm::NodeAttrs& attrs, | ||
const OpContext &ctx, | ||
const std::vector<TBlob> &inputs, | ||
const std::vector<OpReqType> &req, | ||
const std::vector<TBlob> &outputs) { | ||
using namespace mshadow; | ||
using namespace mxnet_op; | ||
CHECK(inputs.size() == 2U || inputs.size() == 3U); | ||
CHECK_EQ(outputs.size(), 1U); | ||
CHECK_EQ(req.size(), 1U); | ||
CHECK_EQ(req[0], kWriteInplace) | ||
<< "Only WriteInplace is supported for npi_boolean_assign"; | ||
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Stream<cpu>* s = ctx.get_stream<cpu>(); | ||
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const TBlob& data = inputs[0]; | ||
const TBlob& mask = inputs[1]; | ||
// Get valid_num | ||
size_t valid_num = 0; | ||
size_t mask_size = mask.shape_.Size(); | ||
std::vector<size_t> prefix_sum(mask_size + 1, 0); | ||
MSHADOW_TYPE_SWITCH(mask.type_flag_, MType, { | ||
valid_num = GetValidNumCPU(mask.dptr<MType>(), prefix_sum.data(), mask_size); | ||
}); | ||
// If there's no True in mask, return directly | ||
if (valid_num == 0) return; | ||
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if (inputs.size() == 3U) { | ||
if (inputs[2].shape_.Size() != 1) { | ||
// tensor case, check tensor size with the valid_num | ||
CHECK_EQ(static_cast<size_t>(valid_num), inputs[2].shape_.Size()) | ||
<< "boolean array indexing assignment cannot assign " << inputs[2].shape_.Size() | ||
<< " input values to the " << valid_num << " output values where the mask is true" | ||
<< std::endl; | ||
} | ||
} | ||
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size_t leading = 1U; | ||
size_t middle = mask_size; | ||
size_t trailing = 1U; | ||
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if (inputs.size() == 3U) { | ||
MSHADOW_TYPE_SWITCH(data.type_flag_, DType, { | ||
if (inputs[2].shape_.Size() == 1) { | ||
Kernel<BooleanAssignCPUKernel<true>, cpu>::Launch( | ||
s, valid_num, data.dptr<DType>(), prefix_sum.data(), prefix_sum.size(), | ||
leading, middle, trailing, inputs[2].dptr<DType>()); | ||
} else { | ||
Kernel<BooleanAssignCPUKernel<false>, cpu>::Launch( | ||
s, valid_num, data.dptr<DType>(), prefix_sum.data(), prefix_sum.size(), | ||
leading, middle, trailing, inputs[2].dptr<DType>()); | ||
} | ||
}); | ||
} else { | ||
CHECK(attrs.dict.find("value") != attrs.dict.end()) | ||
<< "value needs be provided"; | ||
MSHADOW_TYPE_SWITCH(data.type_flag_, DType, { | ||
Kernel<BooleanAssignCPUKernel<true>, cpu>::Launch( | ||
s, valid_num, data.dptr<DType>(), prefix_sum.data(), prefix_sum.size(), | ||
leading, middle, trailing, static_cast<DType>(std::stod(attrs.dict.at("value")))); | ||
}); | ||
} | ||
} | ||
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NNVM_REGISTER_OP(_npi_boolean_mask_assign_scalar) | ||
.describe(R"code(Scalar version of boolean assign)code" ADD_FILELINE) | ||
.set_num_inputs(2) | ||
.set_num_outputs(1) | ||
.set_attr<nnvm::FListInputNames>("FListInputNames", | ||
[](const NodeAttrs& attrs) { | ||
return std::vector<std::string>{"data", "mask"}; | ||
}) | ||
.set_attr<mxnet::FInferShape>("FInferShape", BooleanAssignShape) | ||
.set_attr<nnvm::FInferType>("FInferType", BooleanAssignType) | ||
.set_attr<FCompute>("FCompute<cpu>", NumpyBooleanAssignForwardCPU) | ||
.set_attr<nnvm::FInplaceOption>("FInplaceOption", | ||
[](const NodeAttrs& attrs) { | ||
return std::vector<std::pair<int, int> >{{0, 0}}; | ||
}) | ||
.set_attr<FResourceRequest>("FResourceRequest", | ||
[](const NodeAttrs& attrs) { | ||
return std::vector<ResourceRequest>{ResourceRequest::kTempSpace}; | ||
}) | ||
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes) | ||
.add_argument("data", "NDArray-or-Symbol", "input") | ||
.add_argument("mask", "NDArray-or-Symbol", "mask") | ||
.add_argument("value", "float", "value to be assigned to masked positions"); | ||
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NNVM_REGISTER_OP(_npi_boolean_mask_assign_tensor) | ||
.describe(R"code(Tensor version of boolean assign)code" ADD_FILELINE) | ||
.set_num_inputs(3) | ||
.set_num_outputs(1) | ||
.set_attr<nnvm::FListInputNames>("FListInputNames", | ||
[](const NodeAttrs& attrs) { | ||
return std::vector<std::string>{"data", "mask", "value"}; | ||
}) | ||
.set_attr<mxnet::FInferShape>("FInferShape", BooleanAssignShape) | ||
.set_attr<nnvm::FInferType>("FInferType", BooleanAssignType) | ||
.set_attr<FCompute>("FCompute<cpu>", NumpyBooleanAssignForwardCPU) | ||
.set_attr<nnvm::FInplaceOption>("FInplaceOption", | ||
[](const NodeAttrs& attrs) { | ||
return std::vector<std::pair<int, int> >{{0, 0}}; | ||
}) | ||
.set_attr<FResourceRequest>("FResourceRequest", | ||
[](const NodeAttrs& attrs) { | ||
return std::vector<ResourceRequest>{ResourceRequest::kTempSpace}; | ||
}) | ||
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes) | ||
.add_argument("data", "NDArray-or-Symbol", "input") | ||
.add_argument("mask", "NDArray-or-Symbol", "mask") | ||
.add_argument("value", "NDArray-or-Symbol", "assignment"); | ||
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} // namespace op | ||
} // namespace mxnet |
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