From b297f93537600760ad6026808fe778cf2667fac6 Mon Sep 17 00:00:00 2001
From: Ke Zhen <keezen@qq.com>
Date: Mon, 2 Jul 2018 12:03:45 +0800
Subject: [PATCH] add conv and pooling module

---
 fastNLP/modules/convolution/AvgPool1d.py | 22 +++++++++++++++++++
 fastNLP/modules/convolution/Conv1d.py    | 28 ++++++++++++++++++++++++
 fastNLP/modules/convolution/MaxPool1d.py | 23 +++++++++++++++++++
 3 files changed, 73 insertions(+)
 create mode 100644 fastNLP/modules/convolution/AvgPool1d.py
 create mode 100644 fastNLP/modules/convolution/Conv1d.py
 create mode 100644 fastNLP/modules/convolution/MaxPool1d.py

diff --git a/fastNLP/modules/convolution/AvgPool1d.py b/fastNLP/modules/convolution/AvgPool1d.py
new file mode 100644
index 00000000..c427fc9a
--- /dev/null
+++ b/fastNLP/modules/convolution/AvgPool1d.py
@@ -0,0 +1,22 @@
+# python: 3.6
+# encoding: utf-8
+
+import torch.nn as nn
+# import torch.nn.functional as F
+
+
+class AvgPool1d(nn.Module):
+    """1-d average pooling module."""
+
+    def __init__(self, kernel_size, stride=None, padding=0,
+                 ceil_mode=False, count_include_pad=True):
+        super(AvgPool1d, self).__init__()
+        self.pool = nn.AvgPool1d(
+            kernel_size=kernel_size,
+            stride=stride,
+            padding=padding,
+            ceil_mode=ceil_mode,
+            count_include_pad=count_include_pad)
+
+    def forward(self, x):
+        return self.pool(x)
diff --git a/fastNLP/modules/convolution/Conv1d.py b/fastNLP/modules/convolution/Conv1d.py
new file mode 100644
index 00000000..60554a24
--- /dev/null
+++ b/fastNLP/modules/convolution/Conv1d.py
@@ -0,0 +1,28 @@
+# python: 3.6
+# encoding: utf-8
+
+import torch.nn as nn
+# import torch.nn.functional as F
+
+
+class Conv1d(nn.Module):
+    """
+    Basic 1-d convolution module.
+    """
+
+    def __init__(self, in_channels, out_channels, kernel_size,
+                 stride=1, padding=0, dilation=1,
+                 groups=1, bias=True):
+        super(Conv1d, self).__init__()
+        self.conv = nn.Conv1d(
+            in_channels=in_channels,
+            out_channels=out_channels,
+            kernel_size=kernel_size,
+            stride=stride,
+            padding=padding,
+            dilation=dilation,
+            groups=groups,
+            bias=bias)
+
+    def forward(self, x):
+        return self.conv(x)
diff --git a/fastNLP/modules/convolution/MaxPool1d.py b/fastNLP/modules/convolution/MaxPool1d.py
new file mode 100644
index 00000000..d1f39395
--- /dev/null
+++ b/fastNLP/modules/convolution/MaxPool1d.py
@@ -0,0 +1,23 @@
+# python: 3.6
+# encoding: utf-8
+
+import torch.nn as nn
+# import torch.nn.functional as F
+
+
+class MaxPool1d(nn.Module):
+    """1-d max-pooling module."""
+
+    def __init__(self, kernel_size, stride=None, padding=0,
+                 dilation=1, return_indices=False, ceil_mode=False):
+        super(MaxPool1d, self).__init__()
+        self.maxpool = nn.MaxPool1d(
+            kernel_size=kernel_size,
+            stride=stride,
+            padding=padding,
+            dilation=dilation,
+            return_indices=return_indices,
+            ceil_mode=ceil_mode)
+
+    def forward(self, x):
+        return self.maxpool(x)