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TensorArtist

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Commits

List of commits on branch master.
Unverified
7654eb026f6d87f64e28ca152d006ef7625b0f45

[dev-mjy] add compatible conv2d and pooling2d

vvacancy committed 7 years ago
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59cede921a2c1fad7e28498708f17ade31996efd

[dev-mjy] add random seed global control

vvacancy committed 7 years ago
Unverified
0ba0f3b2a1429f251fa50c4ca9b1176f25ecdcc3

[dev-mjy] update inference module

vvacancy committed 7 years ago
Unverified
0f564ecd2cc06ef3c2934ff69e35f796b7be6a5b

[dev-mjy] tf.queue

vvacancy committed 7 years ago
Unverified
19d6bdfdbe5c1ea66c6e735a3515af85f4ffa823

[dev-mjy] adapt to new graph editor

vvacancy committed 7 years ago
Unverified
75f7407caa06da08dc46f1427f01839a4b3300fe

[dev-mjy] add more parameter for fb_aug, bug fix in parse_dev

vvacancy committed 7 years ago

README

The README file for this repository.

TensorArtist

How-to-use

  1. Install tensorflow, version v1.0 is required.
  2. Set some environs:
export PATH=PATH_TO_TENSOR_ARTIST/bin:$PATH
export TART_DIR_DATA=PATH_TO_DATA_DIR
export TART_DIR_DUMP=PATH_TO_DUMP_DIR
  1. Goto examples/xxx and run: tart-train desc_xxx.py -d cpu

Design Philosophy

  1. All experiments description contained in a single file.
  2. All parameters stored in global storage, called "core.Environ"
  3. All training/testing process based on a container, called "nn.Env"

A good example is better than a thousand-line documentation, feel free to check examples/ to see how it works.

Thanks:

Contributors:

  • Honghua Dong @dhh1995

And other open-source framework authors, including: