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https://github.com/ROCm/composable_kernel.git
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1ca05a105a
Fix ck4inductor conv instance parsing for NumGroupsToMerge parameter (#6434) ## Summary - Add `num_groups_to_merge` field to `CKGroupedConvFwdOp` dataclass to match the new (#4273) `NumGroupsToMerge` template parameter added to `DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3` - Enable inductor tests by default in Jenkins CI ## Test plan - [x] Built wheel without patch: `test_gen_conv_instances` fails with `TypeError: takes from 47 to 50 positional arguments but 51 were given` - [x] Built wheel with patch: `test_gen_conv_instances` passes
97 lines
2.8 KiB
Python
97 lines
2.8 KiB
Python
# Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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# SPDX-License-Identifier: MIT
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from dataclasses import asdict, dataclass
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from typing import Optional, Tuple
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@dataclass
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class CKGroupedConvFwdOp:
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n_dim_spatial: int
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a_layout: str
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b_layout: str
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ds_layout: Tuple[str]
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e_layout: str
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a_element_dtype: str
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b_element_dtype: str
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acc_dtype: str
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c_shuffle_dtype: str
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ds_element_dtype: Tuple[str]
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e_element_dtype: str
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a_elementwise_op: str
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b_elementwise_op: str
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cde_elementwise_op: str
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conv_forward_specialization: str
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gemm_specialization: str
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block_size: int
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m_per_block: int
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n_per_block: int
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k_per_block: int
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ak1: int
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bk1: int
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m_per_xdl: int
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n_per_xdl: int
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m_xdl_per_wave: int
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n_xdl_per_wave: int
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a_block_transfer_thread_cluster_lengths_ak0_m_ak1: Tuple[int, int, int]
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a_block_transfer_thread_cluster_arrange_order: Tuple[int, int, int]
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a_block_transfer_src_access_order: Tuple[int, int, int]
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a_block_transfer_src_vector_dim: int
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a_block_transfer_src_scalar_per_vector: int
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a_block_transfer_dst_scalar_per_vector_ak1: int
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a_block_lds_extra_m: bool
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b_block_transfer_thread_cluster_lengths_bk0_n_bk1: Tuple[int, int, int]
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b_block_transfer_thread_cluster_arrange_order: Tuple[int, int, int]
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b_block_transfer_src_access_order: Tuple[int, int, int]
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b_block_transfer_src_vector_dim: int
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b_block_transfer_src_scalar_per_vector: int
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b_block_transfer_dst_scalar_per_vector_bk1: int
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b_block_lds_extra_n: bool
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c_shuffle_m_xdl_per_wave_per_shuffle: int
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c_shuffle_n_xdl_per_wave_per_shuffle: int
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cde_block_transfer_cluster_lengths_m_block_m_per_block_n_block_n_per_block: Tuple[ # noqa
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int,
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int,
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int,
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int,
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]
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cde_block_transfer_scalar_per_vector_n_per_block: int
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block_gemm_pipeline_scheduler: str
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block_gemm_pipeline_version: str
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a_compute_dtype: Optional[str] = None
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b_compute_dtype: Optional[str] = None
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direct_load: Optional[bool] = None
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num_groups_to_merge: Optional[int] = None
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def name(self):
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# cpp alias for template instance
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return (
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f"ck_device_grouped_convolution_fwd_multiple_abd_xdl_c_shuffle_v3_"
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f"{self.key_name()}"
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)
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def key_name(self):
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# TBD; must be unique per instance. Intended to use as dict key
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return "_".join(
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[
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"K"
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+ field_name.replace("_", "").lower()
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+ "V"
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+ (
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"x".join(map(str, iter(field_value)))
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if isinstance(field_value, tuple)
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else str(field_value).replace(":", "")
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)
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for field_name, field_value in self.dict_items()
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]
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)
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def dict_items(self):
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return asdict(self).items()
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