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[mxfp8 moe training] integrate triton quant/dequant kernels into mxfp8 all to all #3197

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[mxfp8 moe training] integrate triton quant/dequant kernels into mxfp8 all to all #3197

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36 changes: 15 additions & 21 deletions torchao/prototype/moe_training/kernels/mxfp8/comms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,10 @@
blockwise_barrier,
sync_threads,
)
from torchao.prototype.mx_formats.config import ScaleCalculationMode
from torchao.prototype.mx_formats.kernels import (
triton_mxfp8_dequant_dim0,
triton_to_mxfp8_dim0,
)
from torchao.prototype.mx_formats.mx_tensor import to_dtype, to_mx


Expand Down Expand Up @@ -473,11 +476,9 @@ def forward(
"""
# Quantize input
block_size = 32
input_scales, input_data = to_mx(
input_data, input_scales = triton_to_mxfp8_dim0(
input,
elem_dtype=torch.float8_e4m3fn,
block_size=block_size,
scaling_mode=ScaleCalculationMode.RCEIL,
inner_block_size=block_size,
)

# Dispatch data (async)
Expand All @@ -501,20 +502,17 @@ def forward(
output_data = torch.ops._c10d_functional.wait_tensor(output_data)

# Dequantize output
lowp_dtype = output_data.dtype
hp_dtype = input.dtype
hp_output = to_dtype(
triton_hp_output = triton_mxfp8_dequant_dim0(
output_data,
output_scales.view(torch.float8_e8m0fnu),
lowp_dtype,
block_size,
output_scales,
hp_dtype,
block_size,
)

ctx.input_splits = input_splits
ctx.output_splits = output_splits
ctx.group = group
return hp_output
return triton_hp_output

@staticmethod
def backward(ctx, grad_output_hp):
Expand All @@ -529,11 +527,9 @@ def backward(ctx, grad_output_hp):

# Quantize grad_output
block_size = 32
grad_out_scales, grad_out_data = to_mx(
grad_out_data, grad_out_scales = triton_to_mxfp8_dim0(
grad_output_hp,
elem_dtype=torch.float8_e4m3fn,
block_size=block_size,
scaling_mode=ScaleCalculationMode.RCEIL,
inner_block_size=block_size,
)

# Dispatch data (async)
Expand All @@ -557,13 +553,11 @@ def backward(ctx, grad_output_hp):
grad_input_scales = torch.ops._c10d_functional.wait_tensor(grad_input_scales)

hp_dtype = grad_output_hp.dtype
lowp_dtype = grad_input_data.dtype
grad_input_hp = to_dtype(
grad_input_hp = triton_mxfp8_dequant_dim0(
grad_input_data,
grad_input_scales.view(torch.float8_e8m0fnu),
lowp_dtype,
block_size,
grad_input_scales,
hp_dtype,
block_size,
)
return grad_input_hp, None, None, None

Expand Down
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