{"action":"created","comment":{"url":"https://api.github.com/repos/Lasagne/Lasagne/pulls/comments/29359531","id":29359531,"diff_hunk":"@@ -37,6 +89,97 @@ def conv_output_length(input_length, filter_size,\n \n \n class Conv1DLayer(Layer):\n+    \"\"\"\n+    1D convolutional layer\n+\n+    Performs a 1D convolution on its input and optionally adds a bias and\n+    applies an elementwise nonlinearity.\n+\n+    Parameters\n+    ----------\n+    incoming : a :class:`Layer` instance or a tuple\n+        The layer feeding into this layer, or the expected input shape. The\n+        output of this layer should be a 3D tensor, with shape\n+        ``(batch_size, num_input_channels, input_length)``.\n+\n+    num_filters : int\n+        The number of learnable convolutional filters this layer has.\n+\n+    filter_size : int or tuple of int\n+        An integer or a 1-element tuple specifying the size of the filters.\n+\n+    stride : int or tuple of int\n+        An integer or a 1-element tuple specifying the stride of the\n+        convolution operation.\n+\n+    border_mode : str, one of 'valid', 'full', 'same'\n+        A string indicating the convolution border mode.\n+\n+        If 'valid', the convolution is only computed where the input and the\n+        filter fully overlap.\n+\n+        If 'full', the convolution is computed wherever the input and the\n+        filter overlap by at least one position.\n+\n+        If 'same', the convolution is computed wherever the input and the\n+        filter overlap by at least half the filter size, when the filter size\n+        is odd. In practice, the input is zero-padded with half the filter size\n+        at the beginning and half at the end (or one less than half in the case\n+        of an even filter size). Thisresults in an output length that is the\n+        same as the input length (for both odd and even filter sizes).\n+\n+    untie_biases : bool, default False\n+        If ``False``, the layer will have a bias parameter for channel, which\n+        is shared across all positions in this channel. As a result, the `b`\n+        attribute will be a vector (1D).\n+\n+        If True, the layer will have separate bias parameters for each\n+        position in each channel. As a result, the `b` attribute will be a\n+        matrix (2D).\n+\n+    W : Theano shared variable, numpy array or callable\n+        An initializer for the weights of the layer. This should initialize the\n+        layer weights to a 3D array with shape\n+        ``(num_filters, num_input_channels, filter_length)``.\n+        See :meth:`Layer.create_param` for more information.\n+\n+    b : Theano shared variable, numpy array, callable or None\n+        An initializer for the biases of the layer. If None is provided, the\n+        layer will have no biases. This should initialize the layer biases to\n+        a 1D array with shape ``(num_filters,)`` if `untied_biases` is set to\n+        ``False``. If it is set to ``True``, its shape should be\n+        ``(num_filers, input_length)`` instead.","path":"lasagne/layers/conv.py","position":122,"original_position":122,"commit_id":"ab53139ccdf78b06fb3d8c6d6222414568421657","original_commit_id":"ab53139ccdf78b06fb3d8c6d6222414568421657","user":{"login":"f0k","id":629706,"avatar_url":"https://avatars.githubusercontent.com/u/629706?v=3","gravatar_id":"","url":"https://api.github.com/users/f0k","html_url":"https://github.com/f0k","followers_url":"https://api.github.com/users/f0k/followers","following_url":"https://api.github.com/users/f0k/following{/other_user}","gists_url":"https://api.github.com/users/f0k/gists{/gist_id}","starred_url":"https://api.github.com/users/f0k/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/f0k/subscriptions","organizations_url":"https://api.github.com/users/f0k/orgs","repos_url":"https://api.github.com/users/f0k/repos","events_url":"https://api.github.com/users/f0k/events{/privacy}","received_events_url":"https://api.github.com/users/f0k/received_events","type":"User","site_admin":false},"body":"*num_filters","created_at":"2015-04-29T17:33:27Z","updated_at":"2015-04-29T17:33:27Z","html_url":"https://github.com/Lasagne/Lasagne/pull/221#discussion_r29359531","pull_request_url":"https://api.github.com/repos/Lasagne/Lasagne/pulls/221","_links":{"self":{"href":"https://api.github.com/repos/Lasagne/Lasagne/pulls/comments/29359531"},"html":{"href":"https://github.com/Lasagne/Lasagne/pull/221#discussion_r29359531"},"pull_request":{"href":"https://api.github.com/repos/Lasagne/Lasagne/pulls/221"}}},"pull_request":{"url":"https://api.github.com/repos/Lasagne/Lasagne/pulls/221","id":33955073,"html_url":"https://github.com/Lasagne/Lasagne/pull/221","diff_url":"https://github.com/Lasagne/Lasagne/pull/221.diff","patch_url":"https://github.com/Lasagne/Lasagne/pull/221.patch","issue_url":"https://api.github.com/repos/Lasagne/Lasagne/issues/221","number":221,"state":"open","locked":false,"title":"documentation for convolutional layers + user guide for layers","user":{"login":"benanne","id":43829,"avatar_url":"https://avatars.githubusercontent.com/u/43829?v=3","gravatar_id":"","url":"https://api.github.com/users/benanne","html_url":"https://github.com/benanne","followers_url":"https://api.github.com/users/benanne/followers","following_url":"https://api.github.com/users/benanne/following{/other_user}","gists_url":"https://api.github.com/users/benanne/gists{/gist_id}","starred_url":"https://api.github.com/users/benanne/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/benanne/subscriptions","organizations_url":"https://api.github.com/users/benanne/orgs","repos_url":"https://api.github.com/users/benanne/repos","events_url":"https://api.github.com/users/benanne/events{/privacy}","received_events_url":"https://api.github.com/users/benanne/received_events","type":"User","site_admin":false},"body":"I've only done `lasagne.layers.Conv1DLayer` so far (as well as the `conv_output_length` helper function), but feedback is welcome. I'll do `Conv2DLayer` next and then try to do the alternative convolution layers as well.","created_at":"2015-04-23T13:30:30Z","updated_at":"2015-04-29T17:33:27Z","closed_at":null,"merged_at":null,"merge_commit_sha":"e1e345c3ad2f77534ca7d70885963bb3b4d886dc","assignee":null,"milestone":{"url":"https://api.github.com/repos/Lasagne/Lasagne/milestones/1","html_url":"https://github.com/Lasagne/Lasagne/milestones/First%20release","labels_url":"https://api.github.com/repos/Lasagne/Lasagne/milestones/1/labels","id":908462,"number":1,"title":"First release","description":"Things to do for the first 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