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composable_kernel/dispatcher/tests/test_grouped_conv_codegen.py
Vidyasagar Ananthan 920acd2c12 [rocm-libraries] ROCm/rocm-libraries#5168 (commit 8b5afcb) 
[CK] [CK_Tile] Add GroupConv to Kernel Dispatcher

## Motivation

This PR adds CK Tile group convolution (forward, backward-data,
backward-weight) support to the kernel dispatcher, matching and unifying
with the existing dispatcher GEMM infrastructure in architecture and
usability. The dispatcher provides a unified kernel dispatch system with
both C++ and Python frontends, and until now only supported GEMM
operations. This PR enables framework integrators to use the same
declarative kernel workflow for convolutions as they do for GEMM:
declare kernels, build a registry JIT, select kernels within the
registry at runtime, and dispatch to GPU. Future PRs will include
runtime kernel selection heuristics for autotuning of kernel parameters
based on (problem, hardware arch).

## Technical Details

Grouped convolution support has been added to the CK Tile Dispatcher
with generated_conv_backend.hpp enabling dispatcher.run(in, wei, out,
problem) for all 6 conv variants (fwd/bwdd/bwdw x 2D/3D), runtime
heuristic kernel selection, and GroupedConvKernelKey with full
ConvConfigBase fields. Python side adds parallel JIT via
registry.build(max_workers) and heuristic registry.select(). Includes 7
C++ and 6 Python examples covering all directions with CPU reference
validation, and shared infrastructure improvements (BaseRegistry CRTP,
structured exceptions). As a sanity check, JIT compile times for a
single kernel remains the same and for multiple kernels there is better
parallelism:
Kernels | 1 worker | 8 workers
1 | 7.7 s | 7.7 s
2 | 15.9 s | 8.2 s
4 | 33.4 s | 9.7 s
6 | 52.3 s | 10.2 s

## Test Plan

145 ephemeral unit tests have been added to test basic functionality.
All 30 examples/integration tests run end-to-end on gfx950 (MI350): 7
C++ conv, 7 C++ GEMM, 6 Python conv, 10 Python GEMM. CPU reference
validation for forward, backward-data, and backward-weight (2D) in both
C++ and Python examples pass.

## Test Result

30 examples pass. Peak performance: 132 TFLOPS (Batch-32 forward 56x56),
53 TFLOPS (pointwise 1x1). CPU reference accuracy: max_abs_diff < 0.002
for all directions (fp16 vs fp32 reference).

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
2026-04-09 17:39:35 +00:00

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#!/usr/bin/env python3
# Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
# SPDX-License-Identifier: MIT
"""
TDD tests for codegen/unified_grouped_conv_codegen.py -- grouped convolution code generator.
These tests are written BEFORE the implementation exists.
Run: python3 -m pytest dispatcher/tests/test_grouped_conv_codegen.py -v
"""
import sys
import unittest
from pathlib import Path
from unittest.mock import patch
SCRIPT_DIR = Path(__file__).parent.resolve()
DISPATCHER_DIR = SCRIPT_DIR.parent
sys.path.insert(0, str(DISPATCHER_DIR / "codegen"))
sys.path.insert(0, str(DISPATCHER_DIR / "python"))
from codegen_common import TileConfig, TraitConfigBase # noqa: E402
from unified_grouped_conv_codegen import ( # noqa: E402
GroupedConvVariant,
GroupedConvLayout,
GroupedConvKernelConfig,
GroupedConvTypeMappings,
GroupedConvTraitConfig,
CKTileGroupedConvKernelGenerator,
GroupedConvDispatcherWrapperGenerator,
UnifiedGroupedConvCodegen,
)
# =============================================================================
# TestGroupedConvVariant
# =============================================================================
class TestGroupedConvVariant(unittest.TestCase):
"""Test GroupedConvVariant enum values."""
def test_forward_value(self):
self.assertEqual(GroupedConvVariant.FORWARD.value, "forward")
def test_backward_data_value(self):
self.assertEqual(GroupedConvVariant.BACKWARD_DATA.value, "bwd_data")
def test_backward_weight_value(self):
self.assertEqual(GroupedConvVariant.BACKWARD_WEIGHT.value, "bwd_weight")
def test_all_variants_exist(self):
self.assertIn(GroupedConvVariant.FORWARD, GroupedConvVariant)
self.assertIn(GroupedConvVariant.BACKWARD_DATA, GroupedConvVariant)
self.assertIn(GroupedConvVariant.BACKWARD_WEIGHT, GroupedConvVariant)
# =============================================================================
# TestGroupedConvLayout
# =============================================================================
class TestGroupedConvLayout(unittest.TestCase):
"""Test GroupedConvLayout enum for 1D/2D/3D layouts."""
def test_nhwgc_value(self):
self.assertEqual(GroupedConvLayout.NHWGC.value, "NHWGC")
def test_gkyxc_value(self):
self.assertEqual(GroupedConvLayout.GKYXC.value, "GKYXC")
def test_nhwgk_value(self):
self.assertEqual(GroupedConvLayout.NHWGK.value, "NHWGK")
def test_1d_layouts_exist(self):
"""1D conv layouts (e.g., NWGC, GYXC, NWGK)."""
layouts_1d = [
lay
for lay in GroupedConvLayout
if "W" in lay.value and "H" not in lay.value
]
self.assertGreater(len(layouts_1d), 0)
def test_2d_layouts_exist(self):
"""2D conv layouts (e.g., NHWGC, GKYXC, NHWGK)."""
layouts_2d = [lay for lay in GroupedConvLayout if "HW" in lay.value]
self.assertGreater(len(layouts_2d), 0)
def test_3d_layouts_exist(self):
"""3D conv layouts (e.g., NDHWGC, GDKYXC)."""
layouts_3d = [
lay for lay in GroupedConvLayout if "D" in lay.value or "DHW" in lay.value
]
self.assertGreater(len(layouts_3d), 0)
# =============================================================================
# TestGroupedConvKernelConfig
# =============================================================================
class TestGroupedConvKernelConfig(unittest.TestCase):
"""Test GroupedConvKernelConfig dataclass."""
def _make_tile(self):
return TileConfig(128, 128, 32, 2, 2, 1, 32, 32, 16)
def _make_trait(self):
return GroupedConvTraitConfig(
"mem",
"cshuffle",
"intrawave",
False,
False,
False,
double_smem_buffer=False,
num_groups_to_merge=1,
)
def test_name_contains_grouped_conv_fwd(self):
config = GroupedConvKernelConfig(
tile=self._make_tile(),
trait=self._make_trait(),
variant=GroupedConvVariant.FORWARD,
ndim_spatial=2,
arch="gfx942",
layout=GroupedConvLayout.NHWGC,
vector_sizes=(4, 4, 4),
)
name = config.name("fp16")
self.assertIn("grouped_conv_fwd", name)
def test_name_backward_data_contains_bwd_data(self):
config = GroupedConvKernelConfig(
tile=self._make_tile(),
trait=self._make_trait(),
variant=GroupedConvVariant.BACKWARD_DATA,
ndim_spatial=2,
arch="gfx942",
layout=GroupedConvLayout.NHWGC,
vector_sizes=(4, 4, 4),
)
name = config.name("fp16")
self.assertIn("bwd_data", name)
def test_is_valid_for_arch_supported(self):
config = GroupedConvKernelConfig(
tile=self._make_tile(),
trait=self._make_trait(),
variant=GroupedConvVariant.FORWARD,
ndim_spatial=2,
arch="gfx942",
layout=GroupedConvLayout.NHWGC,
vector_sizes=(4, 4, 4),
)
self.assertTrue(config.is_valid_for_arch("gfx942"))
def test_is_valid_for_arch_unsupported(self):
config = GroupedConvKernelConfig(
tile=self._make_tile(),
trait=self._make_trait(),
variant=GroupedConvVariant.FORWARD,
ndim_spatial=2,
arch="gfx942",
layout=GroupedConvLayout.NHWGC,
vector_sizes=(4, 4, 4),
)
self.assertFalse(config.is_valid_for_arch("gfx600"))
# =============================================================================
# TestGroupedConvTypeMappings
# =============================================================================
class TestGroupedConvTypeMappings(unittest.TestCase):
"""Test GroupedConvTypeMappings class."""
def test_dtype_to_ck_fp16(self):
self.assertEqual(GroupedConvTypeMappings.DTYPE_TO_CK["fp16"], "half_t")
def test_dtype_to_ck_bf16(self):
self.assertIn("bf16", GroupedConvTypeMappings.DTYPE_TO_CK)
def test_dtype_to_ck_fp32(self):
self.assertIn("fp32", GroupedConvTypeMappings.DTYPE_TO_CK)
def test_get_layouts_2d_has_in_wei_out_keys(self):
layouts = GroupedConvTypeMappings.get_layouts(2)
self.assertIn("in", layouts)
self.assertIn("wei", layouts)
self.assertIn("out", layouts)
def test_get_layouts_2d_returns_dict(self):
layouts = GroupedConvTypeMappings.get_layouts(2)
self.assertIsInstance(layouts, dict)
def test_get_layouts_1d(self):
layouts = GroupedConvTypeMappings.get_layouts(1)
self.assertIn("in", layouts)
self.assertIn("wei", layouts)
self.assertIn("out", layouts)
def test_get_layouts_3d(self):
layouts = GroupedConvTypeMappings.get_layouts(3)
self.assertIn("in", layouts)
self.assertIn("wei", layouts)
self.assertIn("out", layouts)
# =============================================================================
# TestCKTileGroupedConvKernelGenerator
# =============================================================================
class TestCKTileGroupedConvKernelGenerator(unittest.TestCase):
"""Test CKTileGroupedConvKernelGenerator.generate()."""
def _make_config(self):
tile = TileConfig(128, 128, 32, 2, 2, 1, 32, 32, 16)
trait = GroupedConvTraitConfig(
"mem",
"cshuffle",
"intrawave",
False,
False,
False,
double_smem_buffer=False,
num_groups_to_merge=1,
)
return GroupedConvKernelConfig(
tile=tile,
trait=trait,
variant=GroupedConvVariant.FORWARD,
ndim_spatial=2,
arch="gfx942",
layout=GroupedConvLayout.NHWGC,
vector_sizes=(4, 4, 4),
)
def test_generate_contains_pragma_once(self):
gen = CKTileGroupedConvKernelGenerator("fp16")
config = self._make_config()
result = gen.generate(config)
self.assertIn("#pragma once", result)
def test_generate_contains_forward_kernel_include(self):
gen = CKTileGroupedConvKernelGenerator("fp16")
config = self._make_config()
result = gen.generate(config)
self.assertIn("grouped_convolution_forward_kernel.hpp", result)
def test_generate_returns_non_empty_string(self):
gen = CKTileGroupedConvKernelGenerator("fp16")
config = self._make_config()
result = gen.generate(config)
self.assertIsInstance(result, str)
self.assertGreater(len(result), 100)
def test_generate_valid_cpp_structure(self):
gen = CKTileGroupedConvKernelGenerator("fp16")
config = self._make_config()
result = gen.generate(config)
self.assertIn("#include", result)
self.assertIn("ck_tile", result)
# =============================================================================
# TestGroupedConvDispatcherWrapperGenerator
# =============================================================================
class TestGroupedConvDispatcherWrapperGenerator(unittest.TestCase):
"""Test GroupedConvDispatcherWrapperGenerator.generate()."""
def _make_config(self):
tile = TileConfig(128, 128, 32, 2, 2, 1, 32, 32, 16)
trait = GroupedConvTraitConfig(
"mem",
"cshuffle",
"intrawave",
False,
False,
False,
double_smem_buffer=False,
num_groups_to_merge=1,
)
return GroupedConvKernelConfig(
tile=tile,
trait=trait,
variant=GroupedConvVariant.FORWARD,
ndim_spatial=2,
arch="gfx942",
layout=GroupedConvLayout.NHWGC,
vector_sizes=(4, 4, 4),
)
def test_generate_contains_dispatcher_registration(self):
gen = GroupedConvDispatcherWrapperGenerator("fp16")
config = self._make_config()
kernel_path = DISPATCHER_DIR / "build" / "generated" / "test_kernel.hpp"
output_dir = DISPATCHER_DIR / "build" / "generated"
result = gen.generate(config, kernel_path, output_dir)
self.assertIn("dispatcher", result)
self.assertIn("KernelKey", result)
self.assertIn("KernelInstancePtr", result)
def test_generate_contains_pragma_once(self):
gen = GroupedConvDispatcherWrapperGenerator("fp16")
config = self._make_config()
kernel_path = DISPATCHER_DIR / "build" / "generated" / "test_kernel.hpp"
output_dir = DISPATCHER_DIR / "build" / "generated"
result = gen.generate(config, kernel_path, output_dir)
self.assertIn("#pragma once", result)
def test_generate_valid_cpp(self):
gen = GroupedConvDispatcherWrapperGenerator("fp16")
config = self._make_config()
kernel_path = DISPATCHER_DIR / "build" / "generated" / "test_kernel.hpp"
output_dir = DISPATCHER_DIR / "build" / "generated"
result = gen.generate(config, kernel_path, output_dir)
self.assertIn("#include", result)
self.assertIn("namespace", result)
# =============================================================================
# TestUnifiedGroupedConvCodegen
# =============================================================================
class TestUnifiedGroupedConvCodegen(unittest.TestCase):
"""Test UnifiedGroupedConvCodegen.generate_all()."""
def test_generate_all_returns_dict_with_expected_keys(self):
output_dir = DISPATCHER_DIR / "build" / "generated" / "grouped_conv"
output_dir.mkdir(parents=True, exist_ok=True)
codegen = UnifiedGroupedConvCodegen(
output_dir=output_dir,
datatype="fp16",
ndim_spatial=2,
gpu_target="gfx942",
)
with patch.object(
codegen,
"_get_configs",
return_value=[], # Mock empty config list for fast test
):
results = codegen.generate_all(parallel=False)
self.assertIn("kernels", results)
self.assertIn("wrappers", results)
self.assertIn("failed", results)
self.assertIsInstance(results["kernels"], list)
self.assertIsInstance(results["wrappers"], list)
self.assertIsInstance(results["failed"], list)
def test_generate_all_with_mock_config_produces_output(self):
output_dir = DISPATCHER_DIR / "build" / "generated" / "grouped_conv_test"
output_dir.mkdir(parents=True, exist_ok=True)
codegen = UnifiedGroupedConvCodegen(
output_dir=output_dir,
datatype="fp16",
ndim_spatial=2,
gpu_target="gfx942",
)
# Use a real config - patch the config source to return one config
tile = TileConfig(128, 128, 32, 2, 2, 1, 32, 32, 16)
trait = GroupedConvTraitConfig(
"mem",
"cshuffle",
"intrawave",
False,
False,
False,
double_smem_buffer=False,
num_groups_to_merge=1,
)
config = GroupedConvKernelConfig(
tile=tile,
trait=trait,
variant=GroupedConvVariant.FORWARD,
ndim_spatial=2,
arch="gfx942",
layout=GroupedConvLayout.NHWGC,
vector_sizes=(4, 4, 4),
)
with patch.object(codegen, "_get_configs", return_value=[config]):
results = codegen.generate_all(parallel=False)
self.assertIsInstance(results, dict)
self.assertIn("kernels", results)
# =============================================================================
# TestSharedImports
# =============================================================================
class TestSharedImports(unittest.TestCase):
"""Verify TileConfig from codegen_common and GroupedConvTraitConfig extends TraitConfigBase."""
def test_tile_config_has_expected_fields(self):
"""TileConfig from codegen_common has tile_m, tile_n, tile_k, etc."""
tc = TileConfig(128, 128, 32, 2, 2, 1, 32, 32, 16)
self.assertEqual(tc.tile_m, 128)
self.assertEqual(tc.tile_n, 128)
self.assertEqual(tc.tile_k, 32)
self.assertEqual(tc.warp_m, 2)
self.assertEqual(tc.warp_n, 2)
self.assertEqual(tc.warp_k, 1)
self.assertEqual(tc.warp_tile_m, 32)
self.assertEqual(tc.warp_tile_n, 32)
self.assertEqual(tc.warp_tile_k, 16)
def test_tile_config_is_from_codegen_common(self):
"""TileConfig used by grouped conv is the same as codegen_common.TileConfig."""
tc = TileConfig(128, 128, 32, 2, 2, 1, 32, 32, 16)
self.assertTrue(tc.is_valid())
def test_grouped_conv_trait_config_extends_trait_config_base(self):
"""GroupedConvTraitConfig extends TraitConfigBase."""
self.assertTrue(issubclass(GroupedConvTraitConfig, TraitConfigBase))
def test_grouped_conv_trait_config_has_double_smem_buffer(self):
"""GroupedConvTraitConfig has double_smem_buffer field."""
trait = GroupedConvTraitConfig(
"mem",
"cshuffle",
"intrawave",
False,
False,
False,
double_smem_buffer=True,
num_groups_to_merge=2,
)
self.assertTrue(trait.double_smem_buffer)
self.assertEqual(trait.num_groups_to_merge, 2)
def test_grouped_conv_trait_config_has_num_groups_to_merge(self):
"""GroupedConvTraitConfig has num_groups_to_merge field."""
trait = GroupedConvTraitConfig(
"mem",
"cshuffle",
"intrawave",
False,
False,
False,
double_smem_buffer=False,
num_groups_to_merge=4,
)
self.assertEqual(trait.num_groups_to_merge, 4)
def test_grouped_conv_trait_config_inherits_base_fields(self):
"""GroupedConvTraitConfig inherits pipeline, epilogue, scheduler from base."""
trait = GroupedConvTraitConfig(
"compv4",
"cshuffle",
"intrawave",
True,
True,
True,
double_smem_buffer=False,
num_groups_to_merge=1,
)
self.assertEqual(trait.pipeline, "compv4")
self.assertEqual(trait.epilogue, "cshuffle")
self.assertEqual(trait.scheduler, "intrawave")
self.assertTrue(trait.pad_m)
self.assertTrue(trait.pad_n)
self.assertTrue(trait.pad_k)
# =============================================================================
# TestTwoStageBwdWeightCodegen
# =============================================================================
def _make_two_stage_config():
"""Helper: create a two-stage bwd_weight config."""
return GroupedConvKernelConfig(
tile=TileConfig(16, 64, 64, 1, 4, 1, 16, 16, 32),
trait=GroupedConvTraitConfig(
pipeline="compv3",
epilogue="cshuffle",
scheduler="intrawave",
pad_m=True,
pad_n=True,
pad_k=True,
two_stage=True,
),
variant=GroupedConvVariant.BACKWARD_WEIGHT,
ndim_spatial=2,
arch="gfx942",
)
class TestTwoStageBwdWeightCodegen(unittest.TestCase):
"""Tests for two-stage backward weight kernel generation."""
def test_kernel_name_contains_2stage(self):
config = _make_two_stage_config()
name = config.name("fp16")
self.assertIn("_2stage", name)
self.assertIn("bwd_weight", name)
def test_single_stage_name_has_no_2stage(self):
config = _make_two_stage_config()
config.trait.two_stage = False
name = config.name("fp16")
self.assertNotIn("_2stage", name)
def test_generate_contains_elementwise_include(self):
config = _make_two_stage_config()
gen = CKTileGroupedConvKernelGenerator(
"fp16", GroupedConvVariant.BACKWARD_WEIGHT
)
code = gen.generate(config)
self.assertIn("elementwise.hpp", code)
def test_generate_contains_workspace_type(self):
config = _make_two_stage_config()
gen = CKTileGroupedConvKernelGenerator(
"fp16", GroupedConvVariant.BACKWARD_WEIGHT
)
code = gen.generate(config)
self.assertIn("WorkspaceDataType", code)
def test_generate_contains_elementwise_kernel(self):
config = _make_two_stage_config()
gen = CKTileGroupedConvKernelGenerator(
"fp16", GroupedConvVariant.BACKWARD_WEIGHT
)
code = gen.generate(config)
self.assertIn("ElementWiseKernel", code)
def test_generate_contains_launch_kernel_time_mask(self):
config = _make_two_stage_config()
gen = CKTileGroupedConvKernelGenerator(
"fp16", GroupedConvVariant.BACKWARD_WEIGHT
)
code = gen.generate(config)
self.assertIn("launch_kernel_time_mask", code)
def test_generate_forces_vector_size_c_to_1(self):
config = _make_two_stage_config()
gen = CKTileGroupedConvKernelGenerator(
"fp16", GroupedConvVariant.BACKWARD_WEIGHT
)
code = gen.generate(config)
self.assertIn("VectorSizeC_TwoStage = 1", code)
def test_generate_contains_workspace_memset(self):
config = _make_two_stage_config()
gen = CKTileGroupedConvKernelGenerator(
"fp16", GroupedConvVariant.BACKWARD_WEIGHT
)
code = gen.generate(config)
self.assertIn("hipMemsetAsync", code)
def test_single_stage_does_not_contain_workspace(self):
config = _make_two_stage_config()
config.trait.two_stage = False
gen = CKTileGroupedConvKernelGenerator(
"fp16", GroupedConvVariant.BACKWARD_WEIGHT
)
code = gen.generate(config)
self.assertNotIn("WorkspaceDataType", code)
self.assertNotIn("ElementWiseKernel", code)
self.assertNotIn("launch_kernel_time_mask", code)
def test_default_configs_include_two_stage(self):
from unified_grouped_conv_codegen import get_default_configs
configs = get_default_configs(
arch="gfx942",
variants=[GroupedConvVariant.BACKWARD_WEIGHT],
ndims=[2],
)
two_stage = [c for c in configs if c.trait.two_stage]
single_stage = [c for c in configs if not c.trait.two_stage]
self.assertGreater(len(two_stage), 0, "Should have two-stage configs")
self.assertGreater(
len(single_stage), 0, "Should still have single-stage configs"
)
if __name__ == "__main__":
unittest.main()
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