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Commit ec5e299c authored by zhuwenwen's avatar zhuwenwen
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Merge tag 'v0.7.3' into v0.7.3-dev

parents 47bd229c ed6e9075
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vllm/model_executor/layers/quantization/neuron_quant.py
View file @ ec5e299c
...@@ -20,6 +20,7 @@ class NeuronQuantConfig(QuantizationConfig): ...@@ -20,6 +20,7 @@ class NeuronQuantConfig(QuantizationConfig):
dequant_dtype: str = "f16", dequant_dtype: str = "f16",
quantize_method: str = "vector_dynamic", quantize_method: str = "vector_dynamic",
) -> None: ) -> None:
super().__init__()
self.quant_dtype = os.getenv("NEURON_QUANT_DTYPE", "s8") self.quant_dtype = os.getenv("NEURON_QUANT_DTYPE", "s8")
if self.quant_dtype not in SUPPORTED_QUANT_DTYPE_LIST: if self.quant_dtype not in SUPPORTED_QUANT_DTYPE_LIST:
raise ValueError( raise ValueError(
......
vllm/model_executor/layers/quantization/ptpc_fp8.py 0 → 100644
View file @ ec5e299c
# SPDX-License-Identifier: Apache-2.0
from typing import Any, Dict, List, Optional
import torch
from torch.nn.parameter import Parameter
from vllm import _custom_ops as ops
from vllm.logger import init_logger
from vllm.model_executor.layers.linear import (LinearBase,
UnquantizedLinearMethod)
from vllm.model_executor.layers.quantization.base_config import (
QuantizeMethodBase)
from vllm.model_executor.layers.quantization.fp8 import (Fp8Config,
Fp8KVCacheMethod,
Fp8LinearMethod)
from vllm.model_executor.layers.quantization.utils.quant_utils import (
is_layer_skipped)
from vllm.model_executor.layers.quantization.utils.w8a8_utils import (
apply_fp8_linear)
from vllm.platforms import current_platform
ACTIVATION_SCHEMES = ["static", "dynamic"]
logger = init_logger(__name__)
class PTPCFp8Config(Fp8Config):
"""Config class for Per-Token-Per-Channel Dynamic Quantization Fp8."""
def __init__(
self,
activation_scheme: str = "dynamic",
ignored_layers: Optional[List[str]] = None,
) -> None:
if not current_platform.is_rocm():
raise ValueError(
"ptpc_fp8 quantization is supported only on ROCm.")
if not current_platform.has_device_capability(94):
raise ValueError(
"ptpc_fp8 quantization is supported only on AMD Instinct MI300 GPUs and newer." # noqa: E501
)
if activation_scheme == "static":
raise ValueError(
"ptpc_fp8 as of now only support dynamic quantization.")
super().__init__(is_checkpoint_fp8_serialized=False,
activation_scheme=activation_scheme,
ignored_layers=ignored_layers)
@classmethod
def get_name(cls) -> str:
return "ptpc_fp8"
@classmethod
def from_config(cls, config: Dict[str, Any]) -> "PTPCFp8Config":
activation_scheme = cls.get_from_keys(config, ["activation_scheme"])
ignored_layers = cls.get_from_keys_or(config, ["ignored_layers"], None)
return cls(activation_scheme=activation_scheme,
ignored_layers=ignored_layers)
def get_quant_method(self, layer: torch.nn.Module,
prefix: str) -> Optional["QuantizeMethodBase"]:
from vllm.attention.layer import Attention # Avoid circular import
if isinstance(layer, LinearBase):
if is_layer_skipped(prefix, self.ignored_layers):
return UnquantizedLinearMethod()
return PTPCFp8LinearMethod(self)
elif isinstance(layer, Attention):
return Fp8KVCacheMethod(self)
return None
class PTPCFp8LinearMethod(Fp8LinearMethod):
"""Linear method for Per-Token and Per-Channel FP8 Quantization.
Only supports loading quantized BF16 model checkpoints with dynamic
activation scaling. To load FP16 model checkpoints, user must specify
to convert the FP16 model weight loading into BF16.
The weight scaling factor will be initialized after
the model weights are loaded.
Limitations:
1. Only support float8_e4m3fnuz data type due to the limitation of
torch._scaled_mm (https://github.com/ROCm/pytorch/blob/8c0504d7f3fb0ee4c278c096a5c3caedb01129fa/aten/src/ATen/native/cuda/Blas.cpp#L1041)
Args:
quant_config: The quantization config.
"""
def __init__(self, quant_config: PTPCFp8Config):
super().__init__(quant_config=quant_config)
# Force weight quantization
self.quant_config.is_checkpoint_fp8_serialized = False
def process_weights_after_loading(self, layer: torch.nn.Module) -> None:
layer.weight = torch.nn.Parameter(layer.weight.data,
requires_grad=False)
assert layer.weight.data.dtype == torch.bfloat16, \
f"Currently torch._scaled_mm (hipBLASLt) rowwise gemm only support output dtype of bfloat16. {str(layer.weight.data.dtype)} is specified." # noqa: E501
# Quantize the weights.
qweight, weight_scale = ops.scaled_fp8_quant(
layer.weight, scale=None, use_per_token_if_dynamic=True)
# Update the layer with the new values.
layer.weight = Parameter(
qweight.t(), requires_grad=False) # Pretranspose the weight
layer.weight_scale = Parameter(weight_scale, requires_grad=False)
layer.input_scale = None
def apply(self,
layer: torch.nn.Module,
x: torch.Tensor,
bias: Optional[torch.Tensor] = None) -> torch.Tensor:
return apply_fp8_linear(input=x,
weight=layer.weight,
weight_scale=layer.weight_scale,
input_scale=None,
input_scale_ub=None,
bias=bias,
cutlass_fp8_supported=False,
use_per_token_if_dynamic=True)
vllm/model_executor/layers/quantization/qqq.py
View file @ ec5e299c
...@@ -39,6 +39,7 @@ class QQQConfig(QuantizationConfig): ...@@ -39,6 +39,7 @@ class QQQConfig(QuantizationConfig):
group_size: int, group_size: int,
is_sym: bool = True, is_sym: bool = True,
) -> None: ) -> None:
super().__init__()
self.weight_bits = weight_bits self.weight_bits = weight_bits
self.group_size = group_size self.group_size = group_size
self.is_sym = is_sym self.is_sym = is_sym
......
vllm/model_executor/layers/quantization/quark/quark.py
View file @ ec5e299c
...@@ -30,6 +30,7 @@ class QuarkConfig(QuantizationConfig): ...@@ -30,6 +30,7 @@ class QuarkConfig(QuantizationConfig):
kv_cache_group: Optional[List[str]] = None, kv_cache_group: Optional[List[str]] = None,
kv_cache_config: Optional[Dict[str, Any]] = None, kv_cache_config: Optional[Dict[str, Any]] = None,
pack_method: str = "reorder"): pack_method: str = "reorder"):
super().__init__()
if kv_cache_group is None: if kv_cache_group is None:
kv_cache_group = [] kv_cache_group = []
self.quant_config = quant_config self.quant_config = quant_config
......
vllm/model_executor/layers/quantization/tpu_int8.py
View file @ ec5e299c
...@@ -21,6 +21,7 @@ class Int8TpuConfig(QuantizationConfig): ...@@ -21,6 +21,7 @@ class Int8TpuConfig(QuantizationConfig):
self, self,
activation_scheme: str = "none", activation_scheme: str = "none",
) -> None: ) -> None:
super().__init__()
if activation_scheme not in ACTIVATION_SCHEMES: if activation_scheme not in ACTIVATION_SCHEMES:
raise ValueError( raise ValueError(
f"Unsupported activation scheme {activation_scheme}") f"Unsupported activation scheme {activation_scheme}")
......
vllm/model_executor/layers/quantization/utils/configs/N=1536,K=1536,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"8": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"16": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"24": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"32": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"48": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"64": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"96": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"128": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"256": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"512": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1024": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1536": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2048": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"3072": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4096": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=1536,K=7168,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"8": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"16": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"24": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"32": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"48": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"64": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"96": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"128": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"256": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"512": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1024": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1536": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2048": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"3072": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4096": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=2048,K=512,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"8": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"16": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"24": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"32": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"48": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"64": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"96": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"128": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"256": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"512": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1024": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 128,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1536": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2048": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"3072": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4096": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=2304,K=7168,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"8": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"16": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"24": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"32": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"48": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"64": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"96": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"128": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
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}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=24576,K=7168,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
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"GROUP_SIZE_M": 8,
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"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=256,K=7168,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
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"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
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},
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"1024": {
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},
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"2048": {
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"3072": {
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"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=3072,K=1536,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 1,
"kpack": 1,
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"2": {
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"8": {
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},
"16": {
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},
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},
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},
"96": {
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},
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},
"512": {
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},
"1024": {
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},
"1536": {
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},
"2048": {
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},
"3072": {
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},
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"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=3072,K=7168,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
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"2": {
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},
"8": {
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},
"16": {
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},
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},
"48": {
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},
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},
"96": {
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},
"128": {
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"GROUP_SIZE_M": 1,
"kpack": 1,
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},
"256": {
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},
"512": {
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"kpack": 1,
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"num_warps": 4
},
"1024": {
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"BLOCK_SIZE_N": 64,
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"kpack": 1,
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},
"1536": {
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},
"2048": {
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},
"3072": {
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"BLOCK_SIZE_N": 64,
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},
"4096": {
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"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=32768,K=512,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 8,
"kpack": 1,
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},
"8": {
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},
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},
"24": {
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"32": {
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},
"48": {
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},
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},
"256": {
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},
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},
"1024": {
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"kpack": 1,
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},
"1536": {
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"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2048": {
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"BLOCK_SIZE_M": 64,
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"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"3072": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
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"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4096": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=36864,K=7168,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 32,
"kpack": 1,
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"num_warps": 4
},
"4": {
"BLOCK_SIZE_K": 128,
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"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 1,
"kpack": 1,
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"num_warps": 4
},
"8": {
"BLOCK_SIZE_K": 128,
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"BLOCK_SIZE_N": 32,
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"kpack": 1,
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"num_warps": 4
},
"16": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"24": {
"BLOCK_SIZE_K": 128,
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"GROUP_SIZE_M": 16,
"kpack": 1,
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"num_warps": 4
},
"32": {
"BLOCK_SIZE_K": 128,
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"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"48": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"64": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"96": {
"BLOCK_SIZE_K": 128,
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"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 1,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"128": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"256": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"512": {
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"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1024": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1536": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2048": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"3072": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4096": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
vllm/model_executor/layers/quantization/utils/configs/N=4096,K=512,device_name=AMD_Instinct_MI300X,dtype=fp8_w8a8,block_shape=[128,128].json 0 → 100644
View file @ ec5e299c
{
"1": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"8": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"16": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"24": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"32": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"48": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"64": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"96": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 32,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 8,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"128": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"256": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 128,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"512": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 128,
"BLOCK_SIZE_N": 32,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1024": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"1536": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 64,
"GROUP_SIZE_M": 16,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"2048": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"3072": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
},
"4096": {
"BLOCK_SIZE_K": 128,
"BLOCK_SIZE_M": 64,
"BLOCK_SIZE_N": 128,
"GROUP_SIZE_M": 32,
"kpack": 1,
"matrix_instr_nonkdim": 16,
"num_warps": 4
}
}
\ No newline at end of file
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