Standardise inputs for the conv1d and add the ability to perform dilations

PiperOrigin-RevId: 232507407

tensorflow/python/ops/nn_ops.py

@@ -3999,14 +3999,16 @@ def fractional_avg_pool_v2(value,
     "`NHWC` for data_format is deprecated, use `NWC` instead",
     warn_once=True,
     data_format="NHWC")
-def conv1d(value=None,
+def conv1d(
-           filters=None,
+    value,
-           stride=None,
+    filters,
-           padding=None,
+    stride,
-           use_cudnn_on_gpu=None,
+    padding,
-           data_format=None,
+    use_cudnn_on_gpu=None,
-           name=None,
+    data_format=None,
-           input=None):  # pylint: disable=redefined-builtin
+    name=None,
+    input=None,  # pylint: disable=redefined-builtin
+    dilations=None):
   r"""Computes a 1-D convolution given 3-D input and filter tensors.
 
   Given an input tensor of shape
@@ -4034,8 +4036,8 @@ def conv1d(value=None,
   Args:
     value: A 3D `Tensor`.  Must be of type `float16`, `float32`, or `float64`.
     filters: A 3D `Tensor`.  Must have the same type as `value`.
-    stride: An `integer`.  The number of entries by which
+    stride: An int or list of `ints` that has length `1` or `3`.  The number of
-      the filter is moved right at each step.
+      entries by which the filter is moved right at each step.
     padding: 'SAME' or 'VALID'
     use_cudnn_on_gpu: An optional `bool`.  Defaults to `True`.
     data_format: An optional `string` from `"NWC", "NCW"`.  Defaults
@@ -4044,6 +4046,10 @@ def conv1d(value=None,
       data as [batch, in_channels, in_width].
     name: A name for the operation (optional).
     input: Alias for value.
+    dilations: An int or list of `ints` that has length `1` or `3` which
+      defaults to 1. The dilation factor for each dimension of input. If set to
+      k > 1, there will be k-1 skipped cells between each filter element on that
+      dimension. Dilations in the batch and depth dimensions must be 1.
 
   Returns:
     A `Tensor`.  Has the same type as input.
@@ -4057,13 +4063,16 @@ def conv1d(value=None,
     if data_format is None or data_format == "NHWC" or data_format == "NWC":
       data_format = "NHWC"
       spatial_start_dim = 1
-      strides = [1, 1, stride, 1]
+      channel_index = 2
     elif data_format == "NCHW" or data_format == "NCW":
       data_format = "NCHW"
       spatial_start_dim = 2
-      strides = [1, 1, 1, stride]
+      channel_index = 1
     else:
       raise ValueError("data_format must be \"NWC\" or \"NCW\".")
+    strides = [1] + _get_sequence(stride, 1, channel_index, "stride")
+    dilations = [1] + _get_sequence(dilations, 1, channel_index, "dilations")
+
     value = array_ops.expand_dims(value, spatial_start_dim)
     filters = array_ops.expand_dims(filters, 0)
     result = gen_nn_ops.conv2d(
@@ -4072,17 +4081,21 @@ def conv1d(value=None,
         strides,
         padding,
         use_cudnn_on_gpu=use_cudnn_on_gpu,
-        data_format=data_format)
+        data_format=data_format,
+        dilations=dilations,
+        name=name)
     return array_ops.squeeze(result, [spatial_start_dim])
 
 
 @tf_export("nn.conv1d", v1=[])
-def conv1d_v2(input,  # pylint: disable=redefined-builtin
+def conv1d_v2(
-              filters,
+    input,  # pylint: disable=redefined-builtin
-              stride,
+    filters,
-              padding,
+    stride,
-              data_format=None,
+    padding,
-              name=None):
+    data_format="NWC",
+    dilations=None,
+    name=None):
   r"""Computes a 1-D convolution given 3-D input and filter tensors.
 
   Given an input tensor of shape
@@ -4110,13 +4123,17 @@ def conv1d_v2(input,  # pylint: disable=redefined-builtin
   Args:
     input: A 3D `Tensor`.  Must be of type `float16`, `float32`, or `float64`.
     filters: A 3D `Tensor`.  Must have the same type as `input`.
-    stride: An `integer`.  The number of entries by which
+    stride: An int or list of `ints` that has length `1` or `3`.  The number of
-      the filter is moved right at each step.
+      entries by which the filter is moved right at each step.
     padding: 'SAME' or 'VALID'
     data_format: An optional `string` from `"NWC", "NCW"`.  Defaults
       to `"NWC"`, the data is stored in the order of
       [batch, in_width, in_channels].  The `"NCW"` format stores
       data as [batch, in_channels, in_width].
+    dilations: An int or list of `ints` that has length `1` or `3` which
+      defaults to 1. The dilation factor for each dimension of input. If set to
+      k > 1, there will be k-1 skipped cells between each filter element on that
+      dimension. Dilations in the batch and depth dimensions must be 1.
     name: A name for the operation (optional).
 
   Returns:
@@ -4125,13 +4142,15 @@ def conv1d_v2(input,  # pylint: disable=redefined-builtin
   Raises:
     ValueError: if `data_format` is invalid.
   """
-  return conv1d(input,  # pylint: disable=redefined-builtin
+  return conv1d(
-                filters,
+      input,  # pylint: disable=redefined-builtin
-                stride,
+      filters,
-                padding,
+      stride,
-                use_cudnn_on_gpu=True,
+      padding,
-                data_format=data_format,
+      use_cudnn_on_gpu=True,
-                name=name)
+      data_format=data_format,
+      name=name,
+      dilations=dilations)
 
 
 def conv1d_transpose(

tensorflow/tools/api/golden/v1/tensorflow.nn.pbtxt

@@ -54,7 +54,7 @@ tf_module {
   }
   member_method {
     name: "conv1d"
-    argspec: "args=[\'value\', \'filters\', \'stride\', \'padding\', \'use_cudnn_on_gpu\', \'data_format\', \'name\', \'input\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+    argspec: "args=[\'value\', \'filters\', \'stride\', \'padding\', \'use_cudnn_on_gpu\', \'data_format\', \'name\', \'input\', \'dilations\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
   }
   member_method {
     name: "conv2d"

tensorflow/tools/api/golden/v2/tensorflow.nn.pbtxt

@@ -50,7 +50,7 @@ tf_module {
   }
   member_method {
     name: "conv1d"
-    argspec: "args=[\'input\', \'filters\', \'stride\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+    argspec: "args=[\'input\', \'filters\', \'stride\', \'padding\', \'data_format\', \'dilations\', \'name\'], varargs=None, keywords=None, defaults=[\'NWC\', \'None\', \'None\'], "
   }
   member_method {
     name: "conv2d"