tutorials | Definitions for interactive Thanos tutorials
kandi X-RAY | tutorials Summary
kandi X-RAY | tutorials Summary
tutorials is a Shell library. tutorials has no bugs, it has a Permissive License and it has low support. However tutorials has 1 vulnerabilities. You can download it from GitHub.
Definitions for interactive Thanos tutorials.
Definitions for interactive Thanos tutorials.
Support
Quality
Security
License
Reuse
Support
tutorials has a low active ecosystem.
It has 13 star(s) with 4 fork(s). There are 9 watchers for this library.
It had no major release in the last 6 months.
There are 2 open issues and 0 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of tutorials is current.
Quality
tutorials has no bugs reported.
Security
tutorials has 1 vulnerability issues reported (0 critical, 1 high, 0 medium, 0 low).
License
tutorials is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
tutorials releases are not available. You will need to build from source code and install.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tutorials
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tutorials
tutorials Key Features
No Key Features are available at this moment for tutorials.
tutorials Examples and Code Snippets
Copy
def make_csv_dataset_v2(
file_pattern,
batch_size,
column_names=None,
column_defaults=None,
label_name=None,
select_columns=None,
field_delim=",",
use_quote_delim=True,
na_value="",
header=True,
num_epochs=
Copy
def experimental_distribute_dataset(self, dataset, options=None):
# pylint: disable=line-too-long
"""Creates `tf.distribute.DistributedDataset` from `tf.data.Dataset`.
The returned `tf.distribute.DistributedDataset` can be iterated over
Copy
def scope(self):
"""Context manager to make the strategy current and distribute variables.
This method returns a context manager, and is used as follows:
>>> strategy = tf.distribute.MirroredStrategy(["GPU:0", "GPU:1"])
>
Community Discussions
No Community Discussions are available at this moment for tutorials.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tutorials
You can download it from GitHub.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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