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|
import torch
from ._common_operator_config_utils import (
_get_binary_op_configs,
_get_bn_configs,
_get_cat_config,
_get_conv_configs,
_get_default_op_configs,
_get_embedding_op_configs,
_get_fixed_qparams_op_configs,
_get_linear_configs,
_get_rnn_op_configs,
_get_share_qparams_op_configs,
_get_tensor_info_op_configs,
)
from .backend_config import BackendConfig, DTypeConfig
__all__ = [
"get_fbgemm_backend_config",
]
# ===================
# | DTYPE CONFIGS |
# ===================
# TODO: For now, these DTypeConfigs are identical to the ones defined in native.py
# In the future, once we support specifying quant_min/quant_max and scale_min/scale_max,
# these will diverge. In particular, for FBGEMM, we will restrict the activation quantized
# values to within [0, 127].
fbgemm_weighted_op_quint8_dtype_config = DTypeConfig(
input_dtype=torch.quint8,
output_dtype=torch.quint8,
weight_dtype=torch.qint8,
bias_dtype=torch.float,
)
fbgemm_default_op_quint8_dtype_config = DTypeConfig(
input_dtype=torch.quint8,
output_dtype=torch.quint8,
)
fbgemm_default_op_fp16_dtype_config = DTypeConfig(
input_dtype=torch.float16,
output_dtype=torch.float16,
weight_dtype=torch.float16,
bias_dtype=torch.float16,
)
fbgemm_default_dynamic_int8_dtype_config = DTypeConfig(
input_dtype=torch.quint8,
output_dtype=torch.float,
weight_dtype=torch.qint8,
bias_dtype=torch.float,
is_dynamic=True,
)
fbgemm_default_dynamic_float16_dtype_config = DTypeConfig(
input_dtype=torch.float16,
output_dtype=torch.float,
weight_dtype=torch.float16,
bias_dtype=torch.float,
is_dynamic=True,
)
fbgemm_weight_only_quint8_dtype_config = DTypeConfig(
input_dtype=torch.float,
output_dtype=torch.float,
weight_dtype=torch.quint8,
)
fbgemm_weight_only_quint4x2_dtype_config = DTypeConfig(
input_dtype=torch.float,
output_dtype=torch.float,
weight_dtype=torch.quint4x2,
)
# =====================
# | BACKEND CONFIGS |
# =====================
def get_fbgemm_backend_config() -> BackendConfig:
"""
Return the `BackendConfig` for PyTorch's native FBGEMM backend.
"""
conv_dtype_configs = [fbgemm_weighted_op_quint8_dtype_config]
linear_dtype_configs = [
fbgemm_weighted_op_quint8_dtype_config,
fbgemm_default_dynamic_int8_dtype_config,
fbgemm_default_dynamic_float16_dtype_config,
]
binary_op_dtype_configs = [fbgemm_default_op_quint8_dtype_config]
default_op_dtype_configs = [fbgemm_default_op_quint8_dtype_config]
fixed_qparams_op_dtype_configs = [fbgemm_default_op_quint8_dtype_config]
share_qparams_op_dtype_configs = [fbgemm_default_op_quint8_dtype_config]
tensor_info_op_dtype_configs = [fbgemm_default_op_quint8_dtype_config]
rnn_op_dtype_configs = [
fbgemm_default_dynamic_int8_dtype_config,
fbgemm_default_dynamic_float16_dtype_config,
]
embedding_op_dtype_configs = [
fbgemm_weight_only_quint8_dtype_config,
fbgemm_weight_only_quint4x2_dtype_config,
]
return (
BackendConfig("fbgemm")
.set_backend_pattern_configs(_get_conv_configs(conv_dtype_configs))
.set_backend_pattern_configs(_get_linear_configs(linear_dtype_configs))
.set_backend_pattern_configs(_get_binary_op_configs(binary_op_dtype_configs))
.set_backend_pattern_config(_get_cat_config(default_op_dtype_configs))
.set_backend_pattern_configs(_get_default_op_configs(default_op_dtype_configs))
.set_backend_pattern_configs(
_get_fixed_qparams_op_configs(fixed_qparams_op_dtype_configs)
)
.set_backend_pattern_configs(
_get_share_qparams_op_configs(share_qparams_op_dtype_configs)
)
.set_backend_pattern_configs(
_get_tensor_info_op_configs(tensor_info_op_dtype_configs)
)
.set_backend_pattern_configs(_get_bn_configs(default_op_dtype_configs))
.set_backend_pattern_configs(_get_rnn_op_configs(rnn_op_dtype_configs))
.set_backend_pattern_configs(
_get_embedding_op_configs(embedding_op_dtype_configs)
)
)
|
