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TE 2.4 ROCm 7.2 Gfx950 numeric tests #404

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TE 2.4 ROCm 7.2 Gfx950 numeric tests #404

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32 changes: 28 additions & 4 deletions tests/pytorch/test_numerics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -639,6 +639,9 @@ def test_gpt_selective_activation_recompute(dtype, bs, model, fp8, recipe, fp8_m
pytest.skip("FP8 parameters are not supported in debug mode.")
if recipe.float8_block_scaling() and not fp8_block_scaling_available:
pytest.skip(reason_for_no_fp8_block_scaling)
if (IS_HIP_EXTENSION and get_device_compute_capability() == (9, 5) and
dtype in (torch.float16, torch.bfloat16) and rocm_attn_backend()[2]):
pytest.skip("Test is not supported on GFX950 with current parameters and CK fused attention backend and non-zero dropout.")

config = model_configs[model]

Expand Down Expand Up @@ -761,6 +764,9 @@ def test_gpt_full_activation_recompute(
pytest.skip("FP8 parameters are not supported in debug mode.")
if recipe.float8_block_scaling() and not fp8_block_scaling_available:
pytest.skip(reason_for_no_fp8_block_scaling)
if (IS_HIP_EXTENSION and get_device_compute_capability() == (9, 5) and
dtype in (torch.float16, torch.bfloat16) and rocm_attn_backend()[2]):
pytest.skip("Test is not supported on GFX950 with current parameters and CK fused attention backend and non-zero dropout.")

config = model_configs[model]
torch.compiler.reset() # avoid cache size limit overflow
Expand Down Expand Up @@ -909,6 +915,10 @@ def _test_e2e_checkpointing(bs, dtype, config, checkpoint=False, steps=10, path=
@pytest.mark.parametrize("bs", batch_sizes)
@pytest.mark.parametrize("model", ["126m"])
def test_gpt_checkpointing(dtype, bs, model):
if (IS_HIP_EXTENSION and get_device_compute_capability() == (9, 5) and
dtype in (torch.float16, torch.bfloat16) and rocm_attn_backend()[2]):
pytest.skip("Test is not supported on GFX950 with current parameters and CK fused attention backend and non-zero dropout.")

config = model_configs[model]
outputs = _test_e2e_checkpointing(bs, dtype, config, checkpoint=False)
outputs_checkpoint = _test_e2e_checkpointing(bs, dtype, config, checkpoint=True)
Expand Down Expand Up @@ -2410,6 +2420,9 @@ def test_gpt_fp8_parameters(dtype, bs, model, recipe):
pytest.skip("FP8 parameters are not supported in debug mode.")
if recipe.float8_block_scaling() and not fp8_block_scaling_available:
pytest.skip(reason_for_no_fp8_block_scaling)
if (IS_HIP_EXTENSION and get_device_compute_capability() == (9, 5) and
dtype in (torch.float16, torch.bfloat16) and rocm_attn_backend()[2]):
pytest.skip("Test is not supported on GFX950 with current parameters and CK fused attention backend and non-zero dropout.")

config = model_configs[model]

Expand Down Expand Up @@ -2561,10 +2574,21 @@ def test_transformer_layer_hidden_states_format(dtype, bs, model):
max_seqlen_kv=config.seq_len,
)

torch.testing.assert_close(
y_bshd,
y_thd.reshape(bs, config.seq_len, config.hidden_size).contiguous(),
)
if IS_HIP_EXTENSION:
# On some GPUs CK fused attention with THD can produce larger error
tols = dtype_tols(dtype)
tols["atol"] = 1e-3
torch.testing.assert_close(
y_bshd,
y_thd.reshape(bs, config.seq_len, config.hidden_size).contiguous(),
**tols,
)
else:

torch.testing.assert_close(
y_bshd,
y_thd.reshape(bs, config.seq_len, config.hidden_size).contiguous(),
)


@pytest.mark.parametrize("dtype", param_types)
Expand Down
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