tf_upgrade_v2 for network/classification/base.py

[ytfksw]

What this patch does to fix the issue.

I converted only the blueoil/network/classification/base.py with the command line tool tf_upgrade_v2 to run on tensorflow2 because there are a lot of targets in the network folder.

Here's what I did:

1. install newest tenosrflow (tensorflow-gpu==1.5.2)
2. Run the upgrade script tf_upgrade_v2
3. Check the upgrade report for warnings and errors
4. Run test (make test)

Link to any relevant issues or pull requests.

• Consider upgrading to TensorFlow 2.0 #479
• https://www.tensorflow.org/guide/upgrade

[ytfksw]

This is the whole convert report:

TensorFlow 2.0 Upgrade Script
-----------------------------
Converted 1 files
Detected 0 issues that require attention
--------------------------------------------------------------------------------
================================================================================
Detailed log follows:

================================================================================
--------------------------------------------------------------------------------
Processing file 'blueoil/networks/classification/base.py'
 outputting to 'blueoil/networks/classification/base.py'
--------------------------------------------------------------------------------

95:13: INFO: `name` passed to `name_scope`. Because you may be re-entering an existing scope, it is not safe to convert automatically,  the v2 name_scope does not support re-entering scopes by name.

95:13: INFO: Renamed 'tf.name_scope' to 'tf.compat.v1.name_scope'
97:29: INFO: Added keywords to args of function 'tf.reduce_sum'
102:33: INFO: Added keywords to args of function 'tf.reduce_mean'
133:29: INFO: Added keywords to args of function 'tf.reduce_min'
133:56: INFO: Added keywords to args of function 'tf.reduce_max'
133:81: INFO: Added keywords to args of function 'tf.reduce_min'
151:64: INFO: Added keywords to args of function 'tf.transpose'
153:8: INFO: tf.summary.image requires manual check. The TF 1.x summary API cannot be automatically migrated to TF 2.0, so symbols have been converted to tf.compat.v1.summary.* and must be migrated manually. Typical usage will only require changes to the summary writing logic, not to individual calls like scalar(). For examples of the new summary API, see the Effective TF 2.0 migration document or check the TF 2.0 TensorBoard tutorials.
153:8: INFO: Renamed 'tf.summary.image' to 'tf.compat.v1.summary.image'
156:83: INFO: Added keywords to args of function 'tf.transpose'
163:20: INFO: tf.summary.image requires manual check. The TF 1.x summary API cannot be automatically migrated to TF 2.0, so symbols have been converted to tf.compat.v1.summary.* and must be migrated manually. Typical usage will only require changes to the summary writing logic, not to individual calls like scalar(). For examples of the new summary API, see the Effective TF 2.0 migration document or check the TF 2.0 TensorBoard tutorials.
163:20: INFO: Renamed 'tf.summary.image' to 'tf.compat.v1.summary.image'
177:32: INFO: Added keywords to args of function 'tf.argmax'
181:20: INFO: Added keywords to args of function 'tf.reduce_any'
193:13: INFO: `name` passed to `name_scope`. Because you may be re-entering an existing scope, it is not safe to convert automatically,  the v2 name_scope does not support re-entering scopes by name.

193:13: INFO: Renamed 'tf.name_scope' to 'tf.compat.v1.name_scope'
197:25: INFO: Renamed 'tf.Print' to 'tf.compat.v1.Print'
197:43: INFO: Added keywords to args of function 'tf.shape'
197:61: INFO: Added keywords to args of function 'tf.argmax'
198:26: INFO: Renamed 'tf.Print' to 'tf.compat.v1.Print'
199:36: INFO: Added keywords to args of function 'tf.shape'
199:55: INFO: Added keywords to args of function 'tf.argmax'
--------------------------------------------------------------------------------

As you can see in the log, there are no issues that need attention.
The log says that we should be careful if you exclude compat.v1 (tf.summary.image, tf.name_scope).

[ytfksw]

tf_upgrade_v2 sometimes changed argment to keyword argument.
I deleted the keyword argument and checking it one by one (01000cc), because the arguments become meaninglessly long .

Because API has changed by changing from tf1 to tf2.
It seems to have been converted to a keyword argument to avoid misunderstanding.

tf.reduce_sum
tf1:https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/reduce_sum

tf.math.reduce_sum(
    input_tensor,
    axis=None,
    keepdims=None,
    name=None,
    reduction_indices=None,
    keep_dims=None
)

tf2:https://www.tensorflow.org/api_docs/python/tf/math/reduce_sum

tf.math.reduce_sum(
    input_tensor, axis=None, keepdims=False, name=None
)

tf.reduce_mean
tf1:https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/reduce_mean

tf.math.reduce_mean(
    input_tensor,
    axis=None,
    keepdims=None,
    name=None,
    reduction_indices=None,
    keep_dims=None
)

tf2:https://www.tensorflow.org/api_docs/python/tf/math/reduce_mean

tf.math.reduce_mean(
    input_tensor, axis=None, keepdims=False, name=None
)

tf.reduce_min
tf1:https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/reduce_min

tf.math.reduce_min(
    input_tensor,
    axis=None,
    keepdims=None,
    name=None,
    reduction_indices=None,
    keep_dims=None
)

tf2:https://www.tensorflow.org/api_docs/python/tf/math/reduce_min

tf.math.reduce_min(
    input_tensor, axis=None, keepdims=False, name=None
)

tf.reduce_max
tf1:https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/reduce_max

tf.math.reduce_max(
    input_tensor,
    axis=None,
    keepdims=None,
    name=None,
    reduction_indices=None,
    keep_dims=None
)

tf2:https://www.tensorflow.org/api_docs/python/tf/math/reduce_max

tf.math.reduce_max(
    input_tensor, axis=None, keepdims=False, name=None
)

tf.transpose
tf1: https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/transpose

tf.transpose(
    a,
    perm=None,
    name='transpose',
    conjugate=False
)

tf2: https://www.tensorflow.org/api_docs/python/tf/transpose

tf.transpose(
    a, perm=None, conjugate=False, name='transpose'
)

tf.argmax
tf1:https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/argmax

tf.math.argmax(
    input,
    axis=None,
    name=None,
    dimension=None,
    output_type=tf.dtypes.int64
)

tf2:https://www.tensorflow.org/api_docs/python/tf/math/argmax

tf.math.argmax(
    input, axis=None, output_type=tf.dtypes.int64, name=None
)

tf.reduce_any
tf1: https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/reduce_any

tf.math.reduce_any(
    input_tensor,
    axis=None,
    keepdims=None,
    name=None,
    reduction_indices=None,
    keep_dims=None
)

tf2: https://www.tensorflow.org/api_docs/python/tf/math/reduce_any

tf.math.reduce_any(
    input_tensor, axis=None, keepdims=False, name=None
)

tf.shape
tf1:https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/shape

tf.shape(
    input,
    name=None,
    out_type=tf.dtypes.int32
)

tf2:https://www.tensorflow.org/api_docs/python/tf/shape

tf.shape(
    input, out_type=tf.dtypes.int32, name=None
)

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[ytfksw]

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