conv2d.h 6.46 KB
Newer Older
Li Zhang's avatar
Li Zhang committed
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
/*
 * Copyright (c) 2022-2023, NVIDIA CORPORATION.  All rights reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "cublasLt.h"
#include "cuda_utils.h"
#include "math.h"
#include "stdio.h"
#include "stdlib.h"
#include <cublas_v2.h>
#include <cuda_fp16.h>
#include <cudnn.h>

lvhan028's avatar
lvhan028 committed
26
namespace turbomind {
Li Zhang's avatar
Li Zhang committed
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
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136

template<typename T>
void conv2d(T*             output,
            const T*       input,
            const T*       kernel,
            const int      batch,
            const int      h,
            const int      w,
            const int      in_channels,
            const int      out_channels,
            const int      kernel_size,
            const int      stride,
            cudnnHandle_t& cudnn_handle)
{
    cudnnDataType_t dataType;
    cudnnDataType_t computeType = CUDNN_DATA_FLOAT;
    float           alpha       = 1.0f;
    float           beta        = 0.0f;
    if (std::is_same<T, half>::value) {
        dataType = CUDNN_DATA_HALF;
    }
#ifdef ENABLE_BF16
    else if (std::is_same<T, __nv_bfloat16>::value) {
        dataType = CUDNN_DATA_BFLOAT16;
    }
#endif
    else {
        dataType = CUDNN_DATA_FLOAT;
    }

    cudnnTensorDescriptor_t      input_descriptor_;
    cudnnTensorDescriptor_t      output_descriptor_;
    cudnnFilterDescriptor_t      kernel_descriptor_;
    cudnnConvolutionDescriptor_t convolution_descriptor_;
    cudnnConvolutionFwdAlgo_t    convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_GEMM;
    // cudnnConvolutionFwdAlgo_t convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM;
    // cudnnConvolutionFwdAlgo_t convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_GEMM;
    // cudnnConvolutionFwdAlgo_t convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_DIRECT;
    // cudnnConvolutionFwdAlgo_t convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_FFT_TILING;
    // cudnnConvolutionFwdAlgo_t convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_FFT;
    // cudnnConvolutionFwdAlgo_t convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_WINOGRAD;
    // cudnnConvolutionFwdAlgo_t convolution_algorithm_ = CUDNN_CONVOLUTION_FWD_ALGO_WINOGRAD_NONFUSED;

    checkCUDNN(cudnnCreateTensorDescriptor(&input_descriptor_));
    checkCUDNN(cudnnSetTensor4dDescriptor(input_descriptor_,
                                          /*format=*/CUDNN_TENSOR_NCHW,
                                          /*dataType=*/dataType,
                                          /*batch_size=*/batch,
                                          /*channels=*/in_channels,
                                          /*image_height=*/h,
                                          /*image_width=*/w));

    checkCUDNN(cudnnCreateTensorDescriptor(&output_descriptor_));
    checkCUDNN(cudnnSetTensor4dDescriptor(output_descriptor_,
                                          /*format=*/CUDNN_TENSOR_NHWC,
                                          /*dataType=*/dataType,
                                          /*batch_size=*/batch,
                                          /*channels=*/out_channels,
                                          /*image_height=*/h / stride,
                                          /*image_width=*/w / stride));

    checkCUDNN(cudnnCreateFilterDescriptor(&kernel_descriptor_));
    checkCUDNN(cudnnSetFilter4dDescriptor(kernel_descriptor_,
                                          /*dataType=*/dataType,
                                          /*format=*/CUDNN_TENSOR_NCHW,
                                          /*out_channels=*/out_channels,
                                          /*in_channels=*/in_channels,
                                          /*kernel_height=*/kernel_size,
                                          /*kernel_width=*/kernel_size));

    checkCUDNN(cudnnCreateConvolutionDescriptor(&convolution_descriptor_));
    checkCUDNN(cudnnSetConvolution2dDescriptor(convolution_descriptor_,
                                               /*pad_height=*/0,
                                               /*pad_width=*/0,
                                               /*vertical_stride=*/stride,
                                               /*horizontal_stride=*/stride,
                                               /*dilation_height=*/1,
                                               /*dilation_width=*/1,
                                               /*mode=*//*CUDNN_CONVOLUTION,*/ CUDNN_CROSS_CORRELATION,
                                               /*computeType=*/computeType));

    /*checkCUDNN(cudnnGetConvolutionForwardAlgorithm(cudnn_handle,
                                                   input_descriptor_,
                                                   kernel_descriptor_,
                                                   convolution_descriptor_,
                                                   output_descriptor_,
                                                   CUDNN_CONVOLUTION_FWD_PREFER_FASTEST,
                                                   0,//memoryLimitInBytes
                                                   &convolution_algorithm_));*/

    checkCUDNN(cudnnConvolutionForward(cudnn_handle,
                                       &alpha,
                                       input_descriptor_,
                                       input,
                                       kernel_descriptor_,
                                       kernel,
                                       convolution_descriptor_,
                                       convolution_algorithm_,
                                       nullptr,
                                       0,
                                       &beta,
                                       output_descriptor_,
                                       output));

    checkCUDNN(cudnnDestroyTensorDescriptor(input_descriptor_));
    checkCUDNN(cudnnDestroyTensorDescriptor(output_descriptor_));
    checkCUDNN(cudnnDestroyFilterDescriptor(kernel_descriptor_));
    checkCUDNN(cudnnDestroyConvolutionDescriptor(convolution_descriptor_));
}

lvhan028's avatar
lvhan028 committed
137
}  // namespace turbomind