* [Refactor]: Change the params in pytest to avoid oom error during ci
* format
* fix
* Update test_example_cast.py
* Update parameters in test_example_cast
* Update test_example_flash_attention.py
* update
* format
* fix
* fix
* format
* Fix CopyNode Lower method to include disable_tma flag in GetCopyInst call
* Refactor flash attention implementation to disable TMA for specific copy and allow TMA for other operations
* attempt to fix lint
* Enhance format script to automatically install tools in need
* Add judgement for small `h_q` in MLA decode examples to improve robustness
* Allow scale as a param in MLA decode examples for better generality
* Fix typo
* fix CI bugs in hopper
* lint fix
* Update bulk_copy.cc
* Refactor bulk copy logic in LowerBulkCopy function
- Removed unnecessary blank lines for improved code readability.
- Enhanced stride validation by checking for null pointers in global stride calculations, ensuring robustness against symbolic strides.
- Updated pass configuration handling in dynamic tile language tests to streamline dynamic alignment and TMA lower pass settings.
* test fix
* ci fix
* Update flash-attention dependencies and clean up example code
- Downgraded `flash-attn` dependency version in `requirements-test.txt` to `<=2.2.0`.
- Removed unused imports and commented-out code in various example files to enhance readability and maintainability.
- Updated the `flashattn` function signature to include default parameters for `block_M`, `block_N`, `num_stages`, and `threads`.
- Cleaned up the `example_mha_fwd_varlen.py` and `example_mha_bwd_wgmma_pipelined.py` files by removing unnecessary comments and improving code clarity.
- Deleted the `example_mha_inference.py` file as it is no longer needed.
* Update CI workflow to remove `--user` flag from pip install commands
- Removed the `--user` flag from the pip install commands in both the development and testing sections of the CI workflow to ensure proper installation of dependencies in the virtual environment.
* Update CI workflow to include `--no-user` flag in pip install commands
- Added the `--no-user` flag to the pip install commands in both the development and testing sections of the CI workflow to ensure dependencies are installed correctly within the virtual environment.
* Update CI workflow to include `--no-user` flag in pip install command for wheel mode
- Added the `--no-user` flag to the pip install command in the wheel mode section of the CI workflow to ensure dependencies are installed correctly within the virtual environment.
* test fix
* avoid conflict with system environments
* test fix
* add commnets
---------
Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>
Co-authored-by: LeiWang1999 <leiwang1999@outlook.com>
* [Example] Update kernel compilation in examples to use @tilelang.jit
- Refactored multiple examples to eliminate the use of `tilelang.compile` for kernel creation, directly invoking the functions instead.
- Added `@tilelang.jit` decorators with appropriate output indices to enhance performance and maintainability.
- Improved code clarity by simplifying the kernel invocation process across various examples, ensuring consistency in how kernels are defined and executed.
* format
* Update example_tilelang_sparse_gqa_decode_varlen_indice.py
* Update example_dequant_gemm_fine_grained.py
* Update example_gemm_autotune.py
---------
Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>
* [Enhancement] Introduce pass_configs parameter for kernel compilation
* Added a new `pass_configs` parameter to the `tilelang.compile` function to allow for more flexible kernel compilation configurations.
* Updated related classes and methods to accommodate the new parameter, ensuring compatibility across the codebase.
* Enhanced the `torch_assert_close` function to include customizable tensor names for better debugging output.
* Refactored input handling in example scripts to streamline the process of obtaining inputs for kernel execution.
* lint fix
* [Refactor] Improve flash attention example and layout comparison logic
- Removed unnecessary annotation for `lse_local_split` in the flash attention example to streamline the code.
- Updated the handling of `lse_local_split` to utilize parallel processing for better performance.
- Refactored kernel compilation and profiling logic to enhance clarity and maintainability in the flash attention example.
- Added a condition in `FragmentNode::IsEqual` to handle broadcast cases, improving the robustness of layout comparisons.
* lint fix
* [Enhancement] Add support for shared memory scope in Fill operation
- Introduced handling for `shared.dyn` and `shared` memory scopes in the Fill operation.
- Implemented parallel operation and layout inference for improved performance in shared memory scenarios.
- Updated thread loop partitioning and vectorization logic to accommodate new memory scope handling.
* [Refactor] Remove deprecated decorator and enhance Cython kernel handling
- Removed the deprecated decorator from the main module and added a new implementation in the utils module for better organization.
- Introduced a pointer map in the Cython kernel adapter to manage pointer arguments, improving runtime shape resolution.
- Updated the Cython kernel wrapper to utilize the new pointer map for handling kernel arguments.
- Enhanced error checking in the tensor utility functions to ensure static shapes are enforced.
- Added a new proxy module for buffer and tensor handling, streamlining the interface for TIR programs.
* [Feature] Add matrix multiplication test and kernel implementation
- Introduced a new test file `test_tilelang_language_ptr.py` that implements a matrix multiplication function using TileLang's primitives.
- The `matmul_test` function defines a kernel for performing tile-level GEMM operations with customizable block sizes and data types.
- Added a `run_matmul` function to compile and execute the kernel, along with a test function to validate the implementation.
- Updated the `proxy.py` file to enhance type handling for buffer and tensor proxies, ensuring compatibility with TIR programs.
- Minor formatting improvements in `deprecated.py` for better readability.
* lint fix
* [Refactor] Update tensor creation in matrix multiplication test
- Replaced `T.Tensor.from_ptr` with `T.make_tensor` in `matmul_test` for improved clarity and consistency.
- Updated imports in `__init__.py` to include `make_tensor`.
- Added `make_tensor` function in `proxy.py` to streamline tensor creation from pointers.
* [Refactor] Update tensor definitions across multiple files
- Replaced instances of `T.Tensor` with updated tensor definitions in various benchmark and example files to enhance consistency and clarity.
- Adjusted tensor shapes and types in functions related to matrix multiplication, attention mechanisms, and other operations.
- Improved documentation in README and example files to reflect changes in tensor usage.
* lint fix
* [Refactor] Update tensor types in attention and matrix multiplication examples
- Replaced instances of `T.Tensor` with `T.SharedTensor` and `T.FragmentTensor` in various attention and matrix multiplication functions to improve consistency and clarity.
- Adjusted tensor definitions in benchmark and example files to align with the new tensor types.
- Enhanced the overall structure and readability of the code by standardizing tensor usage across multiple files.
* lint fix
* [Refactor] Update tensor types in GEMM example and test files
- Replaced instances of `T.Tensor` with `T.LocalTensor` and `T.Buffer` in the GEMM example and related test functions to improve consistency and clarity.
- Enhanced the overall structure of the code by standardizing tensor usage across multiple files, aligning with recent updates in tensor definitions.
* [Refactor] Update tensor usage in customize.py
- Replaced instances of `T.Tensor` with `T.Buffer` in the `reshape` and `view` functions to enhance consistency with recent tensor definitions.
- Improved code clarity by standardizing buffer usage across the file.
* [Refactor] Update tensor types in test_tilelang_transform_annotate_device_regions.py
- Replaced instances of `T.Tensor` with `T.Buffer` in the `before` and `expected` methods of the `TestAnnotateThreadExtent` and `TestAnnotateDeviceScope` classes to enhance consistency with recent tensor definitions.
- Improved code clarity by standardizing buffer usage across the test file.
* [Refactor] Update tensor types to SharedBuffer and FragmentBuffer
- Replaced instances of `T.SharedTensor` and `T.FragmentTensor` with `T.SharedBuffer` and `T.FragmentBuffer` across multiple benchmark, example, and test files to enhance consistency with recent tensor definitions.
- Improved code clarity and structure by standardizing buffer usage in attention and matrix multiplication functions.
* [Refactor] Introduce Tensor alias for Buffer in proxy.py
- Added a new alias `Tensor` for `Buffer` in `proxy.py` to facilitate JIT compilation, ensuring that inputs and outputs are mapped with `torch.Tensor`.
- This change enhances clarity and consistency in tensor usage across the codebase.
* [Refactor] Improve flash attention example and layout comparison logic
- Removed unnecessary annotation for `lse_local_split` in the flash attention example to streamline the code.
- Updated the handling of `lse_local_split` to utilize parallel processing for better performance.
- Refactored kernel compilation and profiling logic to enhance clarity and maintainability in the flash attention example.
- Added a condition in `FragmentNode::IsEqual` to handle broadcast cases, improving the robustness of layout comparisons.
* lint fix
* [Enhancement] Add support for shared memory scope in Fill operation
- Introduced handling for `shared.dyn` and `shared` memory scopes in the Fill operation.
- Implemented parallel operation and layout inference for improved performance in shared memory scenarios.
- Updated thread loop partitioning and vectorization logic to accommodate new memory scope handling.
* refactor code
* enhance tutorial
* Enhance error handling and code generation in CUDA and TileLang components
This commit introduces several improvements across multiple files:
- Added more informative error messages in GEMM layout checks
- Updated CUDA codegen to support more flexible function signature generation
- Improved TMA descriptor initialization and kernel dispatch logic
- Refined library generation and source code parsing utilities
- Enhanced error handling in various adapter and wrapper classes
* Add thread tag validation for warp specialization
Introduce a ThreadTagChecker to validate that a PrimFunc only uses threadIdx.x before applying warp specialization. This prevents unintended transformations on kernels with complex thread binding and provides a clear warning to users about potential issues with warp specialization.
* Update TileLang Profiling and Compilation in Flash Decoding Examples
Refactor the profiling and compilation workflow in two flash decoding example scripts:
- Replace `tilelang.lower()` and `tilelang.Profiler()` with `tilelang.compile()`
- Simplify profiler initialization using `get_profiler()`
- Update method calls to use the new profiler and compiled kernel objects
- Maintain existing performance benchmarking and validation logic
* Refactor and clean up code formatting in TileLang testing and adapter modules
This commit includes several code style and formatting improvements:
- Adjust whitespace and line breaks in test files
- Improve code formatting in CUDA source wrapper and adapter utilities
- Enhance readability of function calls and argument handling
- Remove unnecessary whitespace and standardize indentation
- Simplify function signatures and argument parsing
* Refactor CUDA codegen and improve code formatting
This commit includes several improvements to CUDA code generation and formatting:
- Enhance function signature generation in CodeGenTileLangCUDA
- Improve code formatting and readability in CUDA-related files
- Simplify parameter handling and type annotations
- Clean up whitespace and line breaks in codegen and layout files
---------
Co-authored-by: Ubuntu <dlisuser@h100testl730RPS.xu5snccwrbtejcqqalluoku5hb.xx.internal.cloudapp.net>
* [Dev] Add FlashDecoding example
* [CI][Test] Add test cases for tilelang kernel convolution
* [CI][Test] Add test cases for tilelang kernel FlashAttention
* Reduce the number of stages to ensure the shared memory allocation is valid
* Temporarily remove the dim128 case
* lint
* update einops in requirements-dev.txt
* update einops in requirements-test.txt
* remove einops in requirements-dev.txt
