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[XLA:Python] Modify DLPack behavior with unit dimensions.
As discovered in jax-ml/jax#24680, when a PyTorch tensor has a dimension with size `1`, it seems to report the DLPack stride for that dimension as `1`. This means that even when the torch Tensor is formally row-major, the imported array isn't. This shouldn't really matter (the placement of unit dimensions can be arbitrary!), but in practice (since XLA:CPU ignores layouts - that's another issue that is being worked on!) it can be annoying. This change updates the behavior to always produce row-major layouts for unit dimensions wrt to their neighbors. PiperOrigin-RevId: 696341186
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| Original file line number | Diff line number | Diff line change |
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| /* Copyright 2024 The OpenXLA Authors. | ||
| Licensed 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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| #include "xla/python/dlpack_strides.h" | ||
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| #include <algorithm> | ||
| #include <cstdint> | ||
| #include <limits> | ||
| #include <numeric> | ||
| #include <vector> | ||
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| #include "absl/algorithm/container.h" | ||
| #include "absl/status/statusor.h" | ||
| #include "absl/strings/str_join.h" | ||
| #include "absl/types/span.h" | ||
| #include "xla/util.h" | ||
| #include "tsl/platform/logging.h" | ||
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| namespace xla { | ||
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| absl::StatusOr<std::vector<int64_t>> StridesToLayout( | ||
| absl::Span<int64_t const> dims, absl::Span<int64_t const> strides) { | ||
| CHECK_EQ(dims.size(), strides.size()); | ||
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| // Handle unit dimensions by inserting the previous stride. This has the | ||
| // effect of always producing row-major layouts for unit dimensions, which | ||
| // isn't strictly necessary, but is convenient since XLA defaults to row-major | ||
| // layouts. | ||
| std::vector<int64_t> strides_(strides.size()); | ||
| for (int64_t i = 0; i < strides.size(); ++i) { | ||
| if (i == 0 || dims[i] > 1) { | ||
| strides_[i] = strides[i]; | ||
| } else { | ||
| strides_[i] = strides[i - 1]; | ||
| } | ||
| } | ||
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| std::vector<int64_t> minor_to_major(dims.size()); | ||
| std::iota(minor_to_major.begin(), minor_to_major.end(), 0); | ||
| absl::c_sort(minor_to_major, [&](int a, int b) { | ||
| if (strides_[a] < strides_[b]) { | ||
| return true; | ||
| } | ||
| if (strides_[a] > strides_[b]) { | ||
| return false; | ||
| } | ||
| // If two dimensions have the same stride, prefer the major-to-minor | ||
| // interpretation of the ordering, since that's what JAX wants. | ||
| return b < a; | ||
| }); | ||
| int64_t stride = 1; | ||
| for (int64_t d : minor_to_major) { | ||
| if (dims[d] > 1 && strides[d] != stride) { | ||
| return Unimplemented( | ||
| "Only DLPack tensors with trivial (compact) striding are supported; " | ||
| "i.e., tensors whose striding represents a transposition of the " | ||
| "underlying buffer but not broadcasting. Dimensions were: [%s], " | ||
| "strides were [%s].", | ||
| absl::StrJoin(dims, ","), absl::StrJoin(strides, ",")); | ||
| } | ||
| stride *= dims[d]; | ||
| } | ||
| return minor_to_major; | ||
| } | ||
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| } // namespace xla |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,32 @@ | ||
| /* Copyright 2024 The OpenXLA Authors. | ||
| Licensed 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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| #ifndef XLA_PYTHON_DLPACK_STRIDES_H_ | ||
| #define XLA_PYTHON_DLPACK_STRIDES_H_ | ||
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| #include <cstdint> | ||
| #include <vector> | ||
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| #include "absl/status/statusor.h" | ||
| #include "absl/types/span.h" | ||
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| namespace xla { | ||
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| absl::StatusOr<std::vector<int64_t>> StridesToLayout( | ||
| absl::Span<int64_t const> dims, absl::Span<int64_t const> strides); | ||
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| } // namespace xla | ||
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| #endif // XLA_PYTHON_DLPACK_STRIDES_H_ |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,73 @@ | ||
| /* Copyright 2024 The OpenXLA Authors. | ||
| Licensed 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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| #include "xla/python/dlpack_strides.h" | ||
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| #include <cstdint> | ||
| #include <vector> | ||
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| #include "absl/types/span.h" | ||
| #include "tsl/platform/test.h" | ||
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| namespace xla { | ||
| namespace { | ||
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| TEST(DlpackStridesTest, basic) { | ||
| std::vector<int64_t> dims = {2, 3, 4}; | ||
| std::vector<int64_t> strides = {12, 4, 1}; | ||
| auto layout = StridesToLayout(absl::MakeSpan(dims), absl::MakeSpan(strides)); | ||
| EXPECT_TRUE(layout.ok()); | ||
| EXPECT_EQ(layout.value(), std::vector<int64_t>({2, 1, 0})); | ||
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| std::vector<int64_t> strides_cm = {1, 2, 6}; | ||
| auto layout_cm = | ||
| StridesToLayout(absl::MakeSpan(dims), absl::MakeSpan(strides_cm)); | ||
| EXPECT_TRUE(layout_cm.ok()); | ||
| EXPECT_EQ(layout_cm.value(), std::vector<int64_t>({0, 1, 2})); | ||
| } | ||
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| TEST(DlpackStridesTest, unitDim) { | ||
| // Row-major | ||
| std::vector<int64_t> dims = {2, 1, 3, 4}; | ||
| std::vector<int64_t> strides = {12, 12, 4, 1}; | ||
| auto layout = StridesToLayout(absl::MakeSpan(dims), absl::MakeSpan(strides)); | ||
| EXPECT_TRUE(layout.ok()); | ||
| EXPECT_EQ(layout.value(), std::vector<int64_t>({3, 2, 1, 0})); | ||
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| std::vector<int64_t> strides2 = {12, 1, 4, 1}; | ||
| auto layout2 = | ||
| StridesToLayout(absl::MakeSpan(dims), absl::MakeSpan(strides2)); | ||
| EXPECT_TRUE(layout2.ok()); | ||
| EXPECT_EQ(layout2.value(), std::vector<int64_t>({3, 2, 1, 0})); | ||
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| // Column-major. Note that in these cases, since one of the dimensions is 1, | ||
| // there are several valid layouts that we could produce. We choose to prefer | ||
| // row-major whenever there are multiple valid layouts, so the output layouts | ||
| // here aren't completely column-major. | ||
| std::vector<int64_t> strides_cm = {1, 2, 2, 6}; | ||
| auto layout_cm = | ||
| StridesToLayout(absl::MakeSpan(dims), absl::MakeSpan(strides_cm)); | ||
| EXPECT_TRUE(layout_cm.ok()); | ||
| EXPECT_EQ(layout_cm.value(), std::vector<int64_t>({1, 0, 2, 3})); | ||
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| std::vector<int64_t> strides2_cm = {1, 1, 2, 6}; | ||
| auto layout2_cm = | ||
| StridesToLayout(absl::MakeSpan(dims), absl::MakeSpan(strides2_cm)); | ||
| EXPECT_TRUE(layout2_cm.ok()); | ||
| EXPECT_EQ(layout2_cm.value(), std::vector<int64_t>({1, 0, 2, 3})); | ||
| } | ||
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| } // namespace | ||
| } // namespace xla |