mirror of
https://github.com/tile-ai/tilelang.git
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174fbe1908
* Refactor CUDA vectorized cast generation and remove unsupported FP8 type * test fix * lint fix * Refactor CUDA vectorized cast function naming for clarity * Add support for float4_e2m1fn type conversions in CUDA vectorized casts - Implemented conversions between float4_e2m1fn and float32, half2, and float2 in utils.cc and cuda_fp4.h. - Updated test_tilelang_language_vectorized_cast.py to validate new conversions and ensure correctness. - Enhanced dtype conversion in dtypes.py to handle float4_e2m1fn appropriately, logging a warning for unsupported types in PyTorch. * Enhance vectorized cast tests for new data types - Added tests for vectorized casting of float8 and float4 data types, ensuring compatibility with CUDA compute versions. - Refactored existing test functions to improve clarity and organization, separating tests for different data types. - Updated parameterization to include additional test cases for new conversions. --------- Co-authored-by: LeiWang1999 <leiwang1999@outlook.com> Co-authored-by: Zhiwen Mo <zm125@ic.ac.uk>
126 lines
3.4 KiB
Python
126 lines
3.4 KiB
Python
# type: ignore
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import tilelang
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import tilelang.testing
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import tilelang.language as T
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def debug_print_buffer(M=16, N=16, dtype=T.float16):
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@T.prim_func
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def program(Q: T.Tensor((M, N), dtype)):
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with T.Kernel(4, 4, 2, threads=128 * 2) as (bx, by, bz):
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shared_buf = T.alloc_shared([M, N], dtype)
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T.print(shared_buf)
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jit_kernel = tilelang.compile(program)
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profiler = jit_kernel.get_profiler()
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profiler.run_once()
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def test_debug_print_buffer():
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debug_print_buffer(dtype=T.int8)
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debug_print_buffer(dtype=T.int16)
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debug_print_buffer(dtype=T.int32)
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debug_print_buffer(dtype=T.int64)
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debug_print_buffer(dtype=T.uint8)
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debug_print_buffer(dtype=T.uint16)
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debug_print_buffer(dtype=T.uint32)
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debug_print_buffer(dtype=T.uint64)
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debug_print_buffer(dtype=T.float16)
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debug_print_buffer(dtype=T.float32)
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debug_print_buffer(dtype=T.float64)
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debug_print_buffer(dtype=T.bfloat16)
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@tilelang.testing.requires_cuda
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def test_debug_print_buffer_cuda_fp8():
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debug_print_buffer(dtype=T.float8_e4m3fn)
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debug_print_buffer(dtype=T.float8_e5m2)
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@tilelang.testing.requires_rocm
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def test_debug_print_buffer_rocm_fp8():
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debug_print_buffer(dtype=T.float8_e4m3fnuz)
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debug_print_buffer(dtype=T.float8_e5m2fnuz)
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def debug_print_buffer_conditional(M=16, N=16):
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dtype = T.float16
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@T.prim_func
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def program(Q: T.Tensor((M, N), dtype)):
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with T.Kernel(4, 4, 2, threads=128 * 2) as (bx, by, bz):
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shared_buf = T.alloc_shared([M, N], dtype)
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if bx == 0 and by == 0 and bz == 0:
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T.print(shared_buf)
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jit_kernel = tilelang.compile(program, target="cuda")
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profiler = jit_kernel.get_profiler()
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profiler.run_once()
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def test_debug_print_buffer_conditional():
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debug_print_buffer_conditional(16, 16)
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def debug_print_value_conditional(M=16, N=16):
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dtype = T.float16
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@T.prim_func
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def program(Q: T.Tensor((M, N), dtype)):
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with T.Kernel(4, 4, 2, threads=128 * 2) as (bx, by, bz):
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tid = T.get_thread_binding()
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if tid == 0:
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T.print(bx + by + bz)
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jit_kernel = tilelang.compile(program, target="cuda")
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profiler = jit_kernel.get_profiler()
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profiler.run_once()
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def test_debug_print_value_conditional():
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debug_print_value_conditional(16, 16)
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def debug_print_register_files(M=16, N=16):
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dtype = T.float16
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@T.prim_func
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def program(Q: T.Tensor((M, N), dtype)):
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with T.Kernel(4, 4, 2, threads=128 * 2) as (bx, by, bz):
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register_buf = T.alloc_fragment([M, N], dtype)
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for i, j in T.Parallel(M, N):
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T.print(register_buf[i, j])
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jit_kernel = tilelang.compile(program, target="cuda")
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profiler = jit_kernel.get_profiler()
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profiler.run_once()
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def test_debug_print_register_files():
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debug_print_register_files(16, 16)
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def debug_print_msg(M=16, N=16):
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dtype = T.float16
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@T.prim_func
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def program(Q: T.Tensor((M, N), dtype)):
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with T.Kernel(4, 4, 2, threads=128 * 2) as (bx, by, bz):
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tid = T.get_thread_binding()
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if tid == 0:
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T.print(bx + by + bz, msg="hello world")
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jit_kernel = tilelang.compile(program, target="cuda")
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profiler = jit_kernel.get_profiler()
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profiler.run_once()
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def test_debug_print_msg():
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debug_print_msg(16, 16)
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if __name__ == "__main__":
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tilelang.testing.main()
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