217 lines
7.9 KiB
C++
217 lines
7.9 KiB
C++
/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "mlir-hlo/Dialect/mhlo/IR/hlo_ops_common.h"
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#include "llvm/ADT/STLExtras.h"
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#include "llvm/ADT/StringSet.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/IR/BuiltinAttributes.h"
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#include "mlir/IR/BuiltinTypes.h"
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namespace mlir {
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namespace hlo {
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// Verifies the source target pairs attached to collective permute.
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LogicalResult VerifyCollectivePermuteSourceTargetPairs(
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Operation *op, DenseIntElementsAttr attr) {
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auto type = attr.getType().dyn_cast<RankedTensorType>();
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if (type.getRank() != 2)
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return op->emitError() << "expect source_target_pairs attribute to be of "
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"rank 2, but got rank "
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<< type.getRank();
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if (type.getShape()[1] != 2)
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return op->emitError()
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<< "expect source_target_pairs attribute of shape (N, 2), but got ("
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<< type.getShape() << ")";
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// Check source target pairs for duplicate sources or targets.
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llvm::DenseSet<int64_t> sources;
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llvm::DenseSet<int64_t> targets;
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for (auto i = attr.begin(), e = attr.end(); i != e; ++i) {
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auto val = (*i).getSExtValue();
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if (i.getIndex() % 2 == 0) {
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bool is_unique = sources.insert(val).second;
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if (!is_unique)
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return op->emitError() << "duplicate sources not allowed.";
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} else {
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bool is_unique = targets.insert(val).second;
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if (!is_unique)
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return op->emitError() << "duplicate targets not allowed.";
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}
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}
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return success();
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}
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namespace {
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// Custom formatting for convolution window attributes.
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void printWindowAttribute(OpAsmPrinter &p, DenseElementsAttr attribute) {
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if (attribute.getType().getElementType().isInteger(/*width=*/1)) {
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// boolean attribute.
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llvm::interleaveComma(attribute.getBoolValues(), p,
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[&](bool b) { p << (b ? 1 : 0); });
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return;
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}
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if (attribute.getType().getRank() == 2) {
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// Padding is Nx2 attribute.
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auto it = attribute.getValues<int64_t>().begin();
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std::vector<std::pair<int64_t, int64_t>> values(attribute.getNumElements() /
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2);
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for (auto &item : values) {
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int64_t first = *it;
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++it;
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int64_t second = *it;
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++it;
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item = {first, second};
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}
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llvm::interleaveComma(
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values, p, [&](const std::pair<int64_t, int64_t> pair) {
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p << '[' << pair.first << ", " << pair.second << ']';
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});
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} else {
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llvm::interleaveComma(attribute.getValues<int64_t>(), p);
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}
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}
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} // namespace
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void printWindowAttributes(OpAsmPrinter &p, Operation *op,
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llvm::Optional<DenseIntElementsAttr> window_strides,
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llvm::Optional<DenseIntElementsAttr> padding,
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llvm::Optional<DenseIntElementsAttr> lhs_dilation,
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llvm::Optional<DenseIntElementsAttr> rhs_dilation,
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llvm::Optional<DenseElementsAttr> window_reversal) {
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using pair_t = std::pair<DenseElementsAttr, StringRef>;
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std::array<pair_t, 5> printed_attributes = {{
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{window_strides ? *window_strides : nullptr, "stride"},
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{padding ? *padding : nullptr, "pad"},
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{lhs_dilation ? *lhs_dilation : nullptr, "lhs_dilate"},
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{rhs_dilation ? *rhs_dilation : nullptr, "rhs_dilate"},
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{window_reversal ? *window_reversal : nullptr, "reverse"},
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}};
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// Do not print attributes that do no exist.
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auto non_null_attributes = llvm::make_filter_range(
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printed_attributes,
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[](const pair_t &a) { return static_cast<bool>(a.first); });
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llvm::interleaveComma(non_null_attributes, p, [&](const pair_t &a) {
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p << a.second << " = [";
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printWindowAttribute(p, a.first);
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p << "]";
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});
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}
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ParseResult parseWindowAttributes(OpAsmParser &parser,
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DenseIntElementsAttr &window_strides,
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DenseIntElementsAttr &padding,
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DenseIntElementsAttr &lhs_dilation,
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DenseIntElementsAttr &rhs_dilation,
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DenseElementsAttr &window_reversal) {
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StringRef attribute_name;
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// Helper to parse an array of the form [ e0, e1, .. ]
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auto parse_array = [&](std::function<ParseResult(void)> parse_element,
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llvm::Optional<size_t> expected_size =
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llvm::None) -> ParseResult {
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if (parser.parseLSquare()) {
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return failure();
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}
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size_t size = 0;
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do {
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if (parse_element()) {
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return failure();
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}
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size++;
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} while (parser.parseOptionalComma().succeeded());
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if (parser.parseRSquare()) {
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return failure();
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}
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if (expected_size && size != *expected_size) {
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return parser.emitError(parser.getCurrentLocation(),
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"Expected array with")
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<< *expected_size << " elements, got " << size
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<< " elements instead";
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}
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return success();
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};
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llvm::StringSet<> allowed_attribute_names{
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{"stride", "pad", "lhs_dilate", "rhs_dilate", "reverse"}};
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while (parser.parseOptionalKeyword(&attribute_name).succeeded()) {
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// Verify that the attribute name is valid and erase it.
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if (!allowed_attribute_names.erase(attribute_name)) {
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return parser.emitError(parser.getCurrentLocation(),
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"Unexpected keyword ")
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<< attribute_name;
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}
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if (parser.parseEqual()) {
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return failure();
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}
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// parse the attribute value. We need to support either 1D and Nx2 array of
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// integers to parse.
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llvm::SmallVector<int64_t> values;
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auto int64_parser = [&]() {
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return parser.parseInteger(values.emplace_back(0));
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};
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if (attribute_name == "pad") {
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// Parse a 2D array of integers.
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auto inner_parser = [&]() {
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return parse_array(int64_parser, /*expected_size=*/2);
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};
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if (parse_array(inner_parser)) {
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return failure();
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}
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const int64_t size = static_cast<int64_t>(values.size());
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// values should be filled with the Nx2 padding values.
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auto ty = RankedTensorType::get({size / 2, 2},
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parser.getBuilder().getIntegerType(64));
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padding = DenseIntElementsAttr::get(ty, values);
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} else {
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// Parse 1D array of integers.
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if (parse_array(int64_parser)) {
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return failure();
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}
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const int64_t size = static_cast<int64_t>(values.size());
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if (attribute_name == "reverse") {
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auto ty = RankedTensorType::get({size},
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parser.getBuilder().getIntegerType(1));
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auto bool_vector = llvm::to_vector<4>(
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llvm::map_range(values, [](int64_t v) { return v != 0; }));
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window_reversal = DenseElementsAttr::get(ty, bool_vector);
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} else {
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auto attr = parser.getBuilder().getI64TensorAttr(values);
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if (attribute_name == "stride") {
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window_strides = attr;
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} else if (attribute_name == "lhs_dilate") {
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lhs_dilation = attr;
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} else if (attribute_name == "rhs_dilate") {
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rhs_dilation = attr;
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} else {
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llvm_unreachable("Unexpected attribute name");
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}
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}
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}
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// continue parsing if there is a comma at the end.
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if (parser.parseOptionalComma().failed()) break;
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}
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return success();
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}
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} // namespace hlo
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} // namespace mlir
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