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[cleanup][1/x] make hp_tensor_to_float8_dynamic only work with hp inputs #1458

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[cleanup][1/x] make hp_tensor_to_float8_dynamic only work with hp inputs #1458

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09821f0
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vkuzo Dec 23, 2024
fb3b255
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vkuzo Dec 23, 2024
e6bc640
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vkuzo Jan 8, 2025
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17 changes: 10 additions & 7 deletions torchao/float8/float8_linear.py
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Original file line number Diff line number Diff line change
Expand Up @@ -312,13 +312,16 @@ def cast_input_to_float8(self, input: torch.Tensor) -> torch.Tensor:
autocast_dtype = torch.get_autocast_gpu_dtype()
input = input.to(autocast_dtype)

assert self.scaling_type_input is ScalingType.DYNAMIC
input_fp8 = hp_tensor_to_float8_dynamic(
input,
self.config.cast_config_input.target_dtype,
self.linear_mm_config,
gemm_input_role=GemmInputRole.INPUT,
)
if tensor_already_casted_to_fp8(input):
input_fp8 = input
else:
assert self.scaling_type_input is ScalingType.DYNAMIC
input_fp8 = hp_tensor_to_float8_dynamic(
input,
self.config.cast_config_input.target_dtype,
self.linear_mm_config,
gemm_input_role=GemmInputRole.INPUT,
)
return input_fp8

def get_weight_scale(self, weight: torch.Tensor) -> Optional[torch.Tensor]:
Expand Down
2 changes: 0 additions & 2 deletions torchao/float8/float8_scaling_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,8 +52,6 @@ def hp_tensor_to_float8_dynamic(
scaling_granularity: Defines the scaling granularity
axiswise_dim: if axiswise granularity is used, defines the dim to scale across
"""
if tensor_already_casted_to_fp8(hp_tensor):
return hp_tensor
scale = tensor_to_scale(
hp_tensor,
float8_dtype,
Expand Down
27 changes: 15 additions & 12 deletions torchao/float8/float8_tensor_parallel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
)

from torchao.float8.config import ScalingType, e4m3_dtype
from torchao.float8.distributed_utils import tensor_already_casted_to_fp8
from torchao.float8.float8_scaling_utils import (
NoopFwToFloat8BwDynamic,
hp_tensor_to_float8_dynamic,
Expand Down Expand Up @@ -46,12 +47,13 @@ def _prepare_input_fn(
input_tensor, device_mesh, input_layouts, run_check=False
)

input_tensor = hp_tensor_to_float8_dynamic(
input_tensor,
mod.config.cast_config_input.target_dtype,
mod.linear_mm_config,
gemm_input_role=GemmInputRole.INPUT,
) # DTensor(Float8Tensor)
if not tensor_already_casted_to_fp8(input_tensor):
input_tensor = hp_tensor_to_float8_dynamic(
input_tensor,
mod.config.cast_config_input.target_dtype,
mod.linear_mm_config,
gemm_input_role=GemmInputRole.INPUT,
) # DTensor(Float8Tensor)

# transform the input layouts to the desired layouts of ColwiseParallel
if input_layouts != desired_input_layouts:
Expand Down Expand Up @@ -104,12 +106,13 @@ def _prepare_input_fn(
input_tensor, device_mesh, input_layouts, run_check=False
)

input_tensor = hp_tensor_to_float8_dynamic(
input_tensor,
mod.config.cast_config_input.target_dtype,
mod.linear_mm_config,
gemm_input_role=GemmInputRole.INPUT,
) # DTensor(Float8Tensor)
if not tensor_already_casted_to_fp8(input_tensor):
input_tensor = hp_tensor_to_float8_dynamic(
input_tensor,
mod.config.cast_config_input.target_dtype,
mod.linear_mm_config,
gemm_input_role=GemmInputRole.INPUT,
) # DTensor(Float8Tensor)

if input_layouts != desired_input_layouts:
input_tensor = input_tensor.redistribute(
Expand Down
4 changes: 3 additions & 1 deletion torchao/float8/stateful_float8_linear.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,7 +153,9 @@ def cast_input_to_float8(self, input: torch.Tensor) -> torch.Tensor:
autocast_dtype = torch.get_autocast_gpu_dtype()
input = input.to(autocast_dtype)

if self.scaling_type_input is ScalingType.DELAYED:
if tensor_already_casted_to_fp8(input):
input_fp8 = input
elif self.scaling_type_input is ScalingType.DELAYED:
scale_fn_name = self.config.delayed_scaling_config.scale_fn_name
_maybe_initialize_amaxes_scales_for_float8_cast(
input,
Expand Down
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