coderabbitai[bot]
commented
3 weeks ago Walkthrough
## Walkthrough This update introduces a new file, `tabulate_multi_device.cc`, which adds functionality to perform and register fusion operations for deep learning models using PyTorch tensors. This involves defining new classes and functions for forward, backward, and gradient computations across multiple devices, and integrating these operations into the existing build system via updates to `CMakeLists.txt`. ## Changes | File | Changes Summary | |----------------------------------------|-----------------------------------------------------------------------------------------------------------------| | `source/op/pt/CMakeLists.txt` | Added `tabulate_multi_device.cc` to the `OP_SRC` variable. | | `source/op/pt/tabulate_multi_device.cc` | Introduced functions and classes for forward, backward, and gradient computations for fusion operations on multiple devices and registered new operations with PyTorch libraries. | ## Sequence Diagram(s) ```mermaid sequenceDiagram participant Developer as Developer participant BuildSys as Build System participant PyTorch as PyTorch Library participant Model as Deep Learning Model Developer->>BuildSys: Modify CMakeLists.txt BuildSys->>tabulate_multi_device.cc: Add to OP_SRC Note over tabulate_multi_device.cc: New functions and classes added for operations Model->>tabulate_multi_device.cc: Request fusion operation A (forward) tabulate_multi_device.cc->>PyTorch: Register TabulateFusionSeAOp PyTorch->>Model: Perform fusion operation A Model->>tabulate_multi_device.cc: Request gradient of fusion operation A (forward) tabulate_multi_device.cc->>PyTorch: Register TabulateFusionSeAGradOp PyTorch->>Model: Compute gradient of fusion operation A Model->>tabulate_multi_device.cc: Request gradient of gradient of fusion operation A (forward) tabulate_multi_device.cc->>PyTorch: Register TabulateFusionSeAGradGradOp PyTorch->>Model: Perform gradient of gradient computation Model->>tabulate_multi_device.cc: Request fusion operation T (forward) tabulate_multi_device.cc->>PyTorch: Register TabulateFusionSeTOp PyTorch->>Model: Perform fusion operation T Model->>tabulate_multi_device.cc: Request fusion operation R (forward) tabulate_multi_device.cc->>PyTorch: Register TabulateFusionSeROp PyTorch->>Model: Perform fusion operation R Model->>tabulate_multi_device.cc: Request attention-based fusion operation (forward) tabulate_multi_device.cc->>PyTorch: Register TabulateFusionSeAttenOp PyTorch->>Model: Perform attention-based fusion operation ```Recent review details
**Configuration used: CodeRabbit UI** **Review profile: CHILL**Commits
Files that changed from the base of the PR and between 9920e57bf62410d6305e0b05a4bad7abfafce7a2 and 1523196543db982a4842981ec8b719ee2fd95b61.Files selected for processing (2)
* source/op/pt/CMakeLists.txt (1 hunks) * source/tests/pt/test_tabulate_fusion_se_t.py (1 hunks)Files not summarized due to errors (1)
* source/tests/pt/test_tabulate_fusion_se_t.py: Error: Message exceeds token limitFiles skipped from review as they are similar to previous changes (1)
* source/op/pt/CMakeLists.txtAdditional comments not posted (6)
source/tests/pt/test_tabulate_fusion_se_t.py (6)
`1681-1702`: **Ensure correctness of forward function testing.** The forward function test checks the shape and value closeness of the result tensor. Confirm that the assertions are robust enough to catch potential discrepancies in the operation's output. --- `1704-1749`: **Review backward function testing for completeness.** The backward function test checks the gradients' shapes and values. Ensure that these tests are comprehensive and cover all scenarios that might affect gradient computation. --- `436-1507`: **Validate tensor reshaping and gradient settings.** The tensors are reshaped and their gradient settings are explicitly defined. Confirm that the reshaping dimensions and gradient requirements are as expected for the operation being tested.Verification successful
--- The gradient settings for the tensors in the provided code snippet are consistent with other tests in the repository. Specifically, the `requires_grad` attribute is set correctly for the tensors used in the tests. - `self.table_info_tensor.requires_grad = False` - `self.table_tensor.requires_grad = False` - `self.em_x_tensor.requires_grad = True` These settings align with the expected behavior for gradient computations in the tests.--- `23-27`: **Check precision setting for floating point comparisons.** The precision settings are different for `float64` and `float32` types. Ensure that these precision levels are appropriate and consistent with other tests in the project. --- `18-19`: **Check conditional test skipping logic.** The test is skipped if `ENABLE_CUSTOMIZED_OP` is false. Ensure that this is the intended behavior, especially if this operation is crucial and should be tested regardless of the configuration.Scripts executed
The following scripts were executed for the analysis: --- Script: ```shell #!/bin/bash # Description: Verify tensor reshaping and gradient settings. # Test: Check for gradient settings consistency in other tests. rg --type python 'requires_grad =' 'source/tests' ``` Length of output: 80 --- --- Script: ```shell #!/bin/bash # Description: Verify tensor reshaping and gradient settings. # Test: Check for gradient settings consistency in other tests. rg --type py 'requires_grad =' source/tests ``` Length of output: 1550Verification successful
--- The `ENABLE_CUSTOMIZED_OP` conditional test skipping logic is consistently used across multiple test files, indicating that it is an intended behavior. - `source/tests/pt/test_tabulate_fusion_se_t.py` - `source/tests/pt/test_tabulate_fusion_se_r.py` - `source/tests/pt/test_tabulate_fusion_se_a.py` - `source/tests/pt/test_tabulate_fusion_se_atten.py` This confirms that the approach to skip tests when `ENABLE_CUSTOMIZED_OP` is not enabled is consistent and likely intentional.--- `28-424`: **Check tensor initialization and reshape operations.** The tensor is reshaped to (8, 174), resulting in a total of 1392 elements. Ensure that the tensor dimensions and the total number of elements are correctly calculated and aligned with the expected use in tests.Scripts executed
The following scripts were executed for the analysis: --- Script: ```shell #!/bin/bash # Description: Verify the condition for skipping tests. # Test: Search for `ENABLE_CUSTOMIZED_OP` usage in other test files. Expect: Consistent usage. rg --type python 'ENABLE_CUSTOMIZED_OP' ``` Length of output: 70 --- --- Script: ```shell #!/bin/bash # Description: Verify the condition for skipping tests. # Test: Search for `ENABLE_CUSTOMIZED_OP` usage in other test files. Expect: Consistent usage. rg --type py 'ENABLE_CUSTOMIZED_OP' ``` Length of output: 1197Verification successful
--- The search results show numerous instances of tensor reshaping logic across various test files, including the file in question (`source/tests/pt/test_tabulate_fusion_se_t.py`). The specific line of interest, where the tensor is reshaped to `(8, 174)`, is explicitly found in the search results: ``` source/tests/pt/test_tabulate_fusion_se_t.py: ).reshape(8, 174) # 1392 ``` Given this, we can verify that the tensor reshaping logic is consistent and the dimensions align with the expected number of elements (8 * 174 = 1392). There is no evidence of a mismatch or inconsistency in the tensor dimensions or the total number of elements. - **File:** `source/tests/pt/test_tabulate_fusion_se_t.py` - **Line:** 424Scripts executed
The following scripts were executed for the analysis: --- Script: ```shell #!/bin/bash # Description: Verify tensor reshaping logic. # Test: Check for similar tensor reshaping logic in other tests or in the operation implementation. rg --type python 'reshape' 'source/tests' ``` Length of output: 70 --- --- Script: ```shell #!/bin/bash # Description: Verify tensor reshaping logic. # Test: Check for similar tensor reshaping logic in other tests or in the operation implementation. rg 'reshape' --type py source/tests ``` Length of output: 117785
codecov[bot]
njzjz
OP: tabulate_multi_device.cc -> tabulate_fusion_se_a & atten & r & t Compile: add compile file Test: source/tests, se_t has no test, and all other ops pass the forward and backward tests.
Summary by CodeRabbit
New Features
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