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taehoonleermlarsen
taehoonlee
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rmlarsen
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Increase docstring consistency (tensorflow#11932)
* Increase docstring consistency * Update util.py * Update tensor_shape.py These comparison examples need parenthesis to work properly. * Update math_ops.py Set values to `start`, `limit`, and `delta`
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Lines changed: 376 additions & 401 deletions

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‎tensorflow/contrib/batching/python/ops/batch_ops.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -67,7 +67,7 @@ def batch_function(num_batch_threads, max_batch_size, batch_timeout_micros,
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So, for example, in the following code
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```
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```python
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@batch_function(1, 2, 3)
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def layer(a):
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return tf.matmul(a, a)

‎tensorflow/contrib/layers/python/layers/layers.py‎

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@@ -1944,7 +1944,7 @@ def gdn(inputs,
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spatial dimensions. It is similar to local response normalization, but much
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more flexible, as `beta` and `gamma` are trainable parameters.
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Arguments:
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Args:
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inputs: Tensor input.
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inverse: If `False` (default), compute GDN response. If `True`, compute IGDN
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response (one step of fixed point iteration to invert GDN; the division

‎tensorflow/python/feature_column/feature_column.py‎

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -1468,11 +1468,11 @@ class _LazyBuilder(object):
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We're trying to use the following `_FeatureColumn`s:
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```python
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bucketized_age = fc.bucketized_column(fc.numeric_column("age"), ...)
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keywords = fc.categorical_column_with_hash_buckets("keywords", ...)
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age_X_keywords = fc.crossed_column([bucketized_age, "keywords"])
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... = linear_model(features,
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[bucketized_age, keywords, age_X_keywords]
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bucketized_age = fc.bucketized_column(fc.numeric_column("age"), ...)
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keywords = fc.categorical_column_with_hash_buckets("keywords", ...)
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age_X_keywords = fc.crossed_column([bucketized_age, "keywords"])
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... = linear_model(features,
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[bucketized_age, keywords, age_X_keywords]
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```
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If we transform each column independently, then we'll get duplication of

‎tensorflow/python/framework/ops.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1238,7 +1238,7 @@ def __init__(self, node_def, g, inputs=None, output_types=None,
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def _create_c_op(self, graph, node_def, inputs, control_inputs):
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"""Creates a TF_Operation.
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Arguments:
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Args:
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graph: a `Graph`.
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node_def: `node_def_pb2.NodeDef` for the operation to create.
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inputs: A list of `Tensor`s (corresponding to scalar inputs) and lists of
@@ -1282,7 +1282,7 @@ def _create_c_op(self, graph, node_def, inputs, control_inputs):
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def _reconstruct_sequence_inputs(self, op_def, inputs, attrs):
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"""Regroups a flat list of input tensors into scalar and sequence inputs.
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Arguments:
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Args:
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op_def: The `op_def_pb2.OpDef` (for knowing the input types)
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inputs: a list of input `Tensor`s to the op.
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attrs: mapping from attr name to `attr_value_pb2.AttrValue` (these define

‎tensorflow/python/framework/tensor_shape.py‎

Lines changed: 59 additions & 43 deletions
Original file line numberDiff line numberDiff line change
@@ -116,11 +116,11 @@ def merge_with(self, other):
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Dimensions are combined as follows:
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```python
119-
Dimension(n) .merge_with(Dimension(n)) == Dimension(n)
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Dimension(n) .merge_with(Dimension(None)) == Dimension(n)
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Dimension(None).merge_with(Dimension(n)) == Dimension(n)
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Dimension(None).merge_with(Dimension(None)) == Dimension(None)
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Dimension(n) .merge_with(Dimension(m)) raises ValueError for n != m
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tf.Dimension(n) .merge_with(tf.Dimension(n)) == tf.Dimension(n)
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tf.Dimension(n) .merge_with(tf.Dimension(None)) == tf.Dimension(n)
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tf.Dimension(None).merge_with(tf.Dimension(n)) == tf.Dimension(n)
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tf.Dimension(None).merge_with(tf.Dimension(None)) == tf.Dimension(None)
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tf.Dimension(n) .merge_with(tf.Dimension(m)) # raises ValueError for n != m
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```
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Args:
@@ -146,10 +146,12 @@ def __add__(self, other):
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Dimensions are summed as follows:
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Dimension(m) + Dimension(n) == Dimension(m + n)
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Dimension(m) + Dimension(None) == Dimension(None)
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Dimension(None) + Dimension(n) == Dimension(None)
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Dimension(None) + Dimension(None) == Dimension(None)
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```python
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tf.Dimension(m) + tf.Dimension(n) == tf.Dimension(m + n)
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tf.Dimension(m) + tf.Dimension(None) == tf.Dimension(None)
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tf.Dimension(None) + tf.Dimension(n) == tf.Dimension(None)
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tf.Dimension(None) + tf.Dimension(None) == tf.Dimension(None)
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```
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Args:
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other: Another Dimension.
@@ -168,10 +170,12 @@ def __sub__(self, other):
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Dimensions are subtracted as follows:
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Dimension(m) - Dimension(n) == Dimension(m - n)
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Dimension(m) - Dimension(None) == Dimension(None)
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Dimension(None) - Dimension(n) == Dimension(None)
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Dimension(None) - Dimension(None) == Dimension(None)
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```python
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tf.Dimension(m) - tf.Dimension(n) == tf.Dimension(m - n)
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tf.Dimension(m) - tf.Dimension(None) == tf.Dimension(None)
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tf.Dimension(None) - tf.Dimension(n) == tf.Dimension(None)
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tf.Dimension(None) - tf.Dimension(None) == tf.Dimension(None)
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```
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Args:
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other: Another Dimension.
@@ -190,11 +194,11 @@ def __mul__(self, other):
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Dimensions are summed as follows:
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```
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Dimension(m) * Dimension(n) == Dimension(m * n)
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Dimension(m) * Dimension(None) == Dimension(None)
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Dimension(None) * Dimension(n) == Dimension(None)
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Dimension(None) * Dimension(None) == Dimension(None)
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```python
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tf.Dimension(m) * tf.Dimension(n) == tf.Dimension(m * n)
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tf.Dimension(m) * tf.Dimension(None) == tf.Dimension(None)
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tf.Dimension(None) * tf.Dimension(n) == tf.Dimension(None)
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tf.Dimension(None) * tf.Dimension(None) == tf.Dimension(None)
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```
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Args:
@@ -214,10 +218,12 @@ def __floordiv__(self, other):
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Dimensions are divided as follows:
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Dimension(m) // Dimension(n) == Dimension(m // n)
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Dimension(m) // Dimension(None) == Dimension(None)
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Dimension(None) // Dimension(n) == Dimension(None)
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Dimension(None) // Dimension(None) == Dimension(None)
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```python
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tf.Dimension(m) // tf.Dimension(n) == tf.Dimension(m // n)
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tf.Dimension(m) // tf.Dimension(None) == tf.Dimension(None)
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tf.Dimension(None) // tf.Dimension(n) == tf.Dimension(None)
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tf.Dimension(None) // tf.Dimension(None) == tf.Dimension(None)
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```
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other: Another `Dimension`.
@@ -250,12 +256,14 @@ def __div__(self, other):
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def __mod__(self, other):
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"""Returns `self` modulo `other.
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Dimension moduli are computed as follows:
259+
Dimension moduli are computed as follows:
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Dimension(m) % Dimension(n) == Dimension(m % n)
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Dimension(m) % Dimension(None) == Dimension(None)
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Dimension(None) % Dimension(n) == Dimension(None)
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Dimension(None) % Dimension(None) == Dimension(None)
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```python
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tf.Dimension(m) % tf.Dimension(n) == tf.Dimension(m % n)
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tf.Dimension(m) % tf.Dimension(None) == tf.Dimension(None)
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tf.Dimension(None) % tf.Dimension(n) == tf.Dimension(None)
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tf.Dimension(None) % tf.Dimension(None) == tf.Dimension(None)
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```
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other: Another Dimension.
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Dimensions are compared as follows:
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Dimension(m) < Dimension(n) == m < n
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Dimension(m) < Dimension(None) == None
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Dimension(None) < Dimension(n) == None
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Dimension(None) < Dimension(None) == None
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```python
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(tf.Dimension(m) < tf.Dimension(n)) == (m < n)
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(tf.Dimension(m) < tf.Dimension(None)) == None
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(tf.Dimension(None) < tf.Dimension(n)) == None
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(tf.Dimension(None) < tf.Dimension(None)) == None
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```
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other: Another Dimension.
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Dimensions are compared as follows:
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Dimension(m) <= Dimension(n) == m <= n
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Dimension(m) <= Dimension(None) == None
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Dimension(None) <= Dimension(n) == None
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Dimension(None) <= Dimension(None) == None
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```python
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(tf.Dimension(m) <= tf.Dimension(n)) == (m <= n)
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(tf.Dimension(m) <= tf.Dimension(None)) == None
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(tf.Dimension(None) <= tf.Dimension(n)) == None
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(tf.Dimension(None) <= tf.Dimension(None)) == None
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```
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other: Another Dimension.
@@ -320,10 +332,12 @@ def __gt__(self, other):
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Dimensions are compared as follows:
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Dimension(m) > Dimension(n) == m > n
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Dimension(m) > Dimension(None) == None
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Dimension(None) > Dimension(n) == None
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Dimension(None) > Dimension(None) == None
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```python
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(tf.Dimension(m) > tf.Dimension(n)) == (m > n)
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(tf.Dimension(m) > tf.Dimension(None)) == None
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(tf.Dimension(None) > tf.Dimension(n)) == None
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(tf.Dimension(None) > tf.Dimension(None)) == None
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```
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other: Another Dimension.
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Dimensions are compared as follows:
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Dimension(m) >= Dimension(n) == m >= n
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Dimension(m) >= Dimension(None) == None
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Dimension(None) >= Dimension(n) == None
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Dimension(None) >= Dimension(None) == None
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```python
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(tf.Dimension(m) >= tf.Dimension(n)) == (m >= n)
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(tf.Dimension(m) >= tf.Dimension(None)) == None
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(tf.Dimension(None) >= tf.Dimension(n)) == None
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(tf.Dimension(None) >= tf.Dimension(None)) == None
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```
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Args:
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other: Another Dimension.

‎tensorflow/python/layers/base.py‎

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@@ -2079,11 +2079,9 @@ def _unique_layer_name(name):
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Example:
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2082-
```
2083-
>>> _unique_layer_name('dense')
2084-
dense_1
2085-
>>> _unique_layer_name('dense')
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dense_2
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```python
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_unique_layer_name('dense') # dense_1
2084+
_unique_layer_name('dense') # dense_2
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```
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"""
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graph = ops.get_default_graph()

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