-
Notifications
You must be signed in to change notification settings - Fork 527
/
Copy pathquantized.yaml
113 lines (95 loc) · 6.08 KB
/
quantized.yaml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
- func: quantized_decomposed::add.out(Tensor a, float a_scale, int a_zero_point, int a_quant_min, int a_quant_max, Tensor b, float b_scale, int b_zero_point, int b_quant_min, int b_quant_max, float out_scale, int out_zero_point, int out_quant_min, int out_quant_max, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_add_out
- func: quantized_decomposed::choose_qparams.Tensor_out(Tensor input, int quant_min, int quant_max, float eps, ScalarType dtype, *, Tensor(a!) scale_out, Tensor(b!) zero_point_out) -> (Tensor(a!), Tensor(b!))
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::choose_qparams_tensor_out
- func: quantized_decomposed::dequantize_per_tensor.out(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype, *, ScalarType? out_dtype=None, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::dequantize_per_tensor_out
- func: quantized_decomposed::dequantize_per_tensor.Tensor_out(Tensor input, Tensor scale, Tensor zero_point, int quant_min, int quant_max, ScalarType dtype, *, ScalarType? out_dtype=None, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::dequantize_per_tensor_tensor_args_out
- func: quantized_decomposed::quantize_per_channel.out(Tensor input, Tensor scales, Tensor zero_points, int axis, int quant_min, int quant_max, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantize_per_channel_out
- func: quantized_decomposed::dequantize_per_channel.out(Tensor input, Tensor scales, Tensor? zero_points, int axis, int quant_min, int quant_max, ScalarType dtype, *, ScalarType? out_dtype=None, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::dequantize_per_channel_out
- func: quantized_decomposed::embedding_byte.out(Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, int weight_quant_min, int weight_quant_max, Tensor indices, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_embedding_byte_out
- func: quantized_decomposed::embedding_byte.dtype_out(Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, int weight_quant_min, int weight_quant_max, Tensor indices, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_embedding_byte_dtype_out
- func: quantized_decomposed::embedding_2bit.out(Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, int weight_quant_min, int weight_quant_max, Tensor indices, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_embedding_2bit_out
- func: quantized_decomposed::embedding_2bit.dtype_out(Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, int weight_quant_min, int weight_quant_max, Tensor indices, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_embedding_2bit_dtype_out
- func: quantized_decomposed::embedding_4bit.out(Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, int weight_quant_min, int weight_quant_max, Tensor indices, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_embedding_4bit_out
- func: quantized_decomposed::embedding_4bit.dtype_out(Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, int weight_quant_min, int weight_quant_max, Tensor indices, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_embedding_4bit_dtype_out
- func: quantized_decomposed::mixed_mm.out(Tensor input, Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_mixed_mm_out
- func: quantized_decomposed::mixed_linear.out(Tensor input, Tensor weight, Tensor weight_scales, Tensor? weight_zero_points, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantized_mixed_linear_out
- func: quantized_decomposed::quantize_per_tensor.out(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantize_per_tensor_out
- func: quantized_decomposed::quantize_per_tensor.Tensor_out(Tensor input, Tensor scale, Tensor zero_point, int quant_min, int quant_max, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantize_per_tensor_tensor_args_out
- func: quantized_decomposed::choose_qparams_per_token_asymmetric.out(Tensor input, ScalarType dtype, *, Tensor(a!) scale_out, Tensor(b!) zero_point_out) -> (Tensor(a!), Tensor(b!))
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::choose_qparams_per_token_asymmetric_out
- func: quantized_decomposed::quantize_per_token.out(Tensor input, Tensor scales, Tensor zero_points, int quant_min, int quant_max, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::quantize_per_token_out
- func: quantized_decomposed::dequantize_per_token.out(Tensor input, Tensor scales, Tensor zero_points, int quant_min, int quant_max, ScalarType dtype, ScalarType output_dtype, *, Tensor(a!) out) -> Tensor(a!)
variants: function
kernels:
- arg_meta: null
kernel_name: torch::executor::dequantize_per_token_out