From 4f3dbd003f004569a916f964caaaf7b9a0a28017 Mon Sep 17 00:00:00 2001 From: Phil Wang Date: Thu, 29 Apr 2021 12:41:00 -0700 Subject: [PATCH] for PiT, project to increased dimensions on first grouped conv for depthwise-conv --- setup.py | 2 +- vit_pytorch/pit.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/setup.py b/setup.py index 0aa5a04..d6744fc 100644 --- a/setup.py +++ b/setup.py @@ -3,7 +3,7 @@ from setuptools import setup, find_packages setup( name = 'vit-pytorch', packages = find_packages(exclude=['examples']), - version = '0.16.12', + version = '0.16.13', license='MIT', description = 'Vision Transformer (ViT) - Pytorch', author = 'Phil Wang', diff --git a/vit_pytorch/pit.py b/vit_pytorch/pit.py index e3e5c3d..166f8e1 100644 --- a/vit_pytorch/pit.py +++ b/vit_pytorch/pit.py @@ -89,8 +89,8 @@ class DepthWiseConv2d(nn.Module): def __init__(self, dim_in, dim_out, kernel_size, padding, stride, bias = True): super().__init__() self.net = nn.Sequential( - nn.Conv2d(dim_in, dim_in, kernel_size = kernel_size, padding = padding, groups = dim_in, stride = stride, bias = bias), - nn.Conv2d(dim_in, dim_out, kernel_size = 1, bias = bias) + nn.Conv2d(dim_in, dim_out, kernel_size = kernel_size, padding = padding, groups = dim_in, stride = stride, bias = bias), + nn.Conv2d(dim_out, dim_out, kernel_size = 1, bias = bias) ) def forward(self, x): return self.net(x)