GitLab

Open source release of Brain Coder.

update supported tf versions for object detection on gcloud.

Fix demo_inference to properly normalize input.

Use temp variable for predictions.

Before the fix the demo_inference.py used batch_norm and it did the
normalization of input image implicitly. If at inference time the
batch_norm was disabled the inference produced incorrect results.
This fix does the proper input image normalization and disables the batch_norm
at inference time.

Revert "Flags"

Update Dockerfile with new bazel version.

Update README.md

Fix AudioSet url

[mnist]: Use FixedLengthRecordDataset

- Prior to this change, the use of tf.data.Dataset essentially embedded
  the entire training/evaluation dataset into the graph as a constant,
  leading to unnecessarily humungous graphs (Fixes #3017)
- Also, use batching on the evaluation dataset to allow
  evaluation on GPUs that cannot fit the entire evaluation dataset in
  memory (Fixes #3046)

Update README.md

Fix typo: "the most is mostly converged" vs "the model is mostly converged"

compatible with tensorflow 1.4.1

Redirect users from cifar10 to cifar10_estimator

Make the redirect to slim notice more prominent

[mnist]: Make flags function scoped (not module scoped).

This will make it easier to share the model definition with
eager execution and TPU demos without any side effects of running
unnecessary code on module import.

[mnist]: Updates

Update blog_custom_estimators.py

Added correct link to blogpost
Changed Sentosa to Setosa in a couple of places

https://github.com/tensorflow/models/pull/3024

Update README.md in adv_imagenet_models.

Add newly released adversarially trained (no ensemble) checkpoint for
Inception Resnet v2.

Add code for Custom Estimators blog post.