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| author | Jules Laplace <julescarbon@gmail.com> | 2020-01-15 22:49:44 +0100 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2020-01-15 22:49:44 +0100 |
| commit | ad434493fe0203e632d7e7abeae0ce339d0a26bb (patch) | |
| tree | 7cba112835ffc34387da73b377684a162aedd077 /cli/app/search/search_dense.py | |
| parent | 0e996eed57590c294f1995b379fb116dee400a1e (diff) | |
params...
Diffstat (limited to 'cli/app/search/search_dense.py')
| -rw-r--r-- | cli/app/search/search_dense.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py index 5aee392..6fba70d 100644 --- a/cli/app/search/search_dense.py +++ b/cli/app/search/search_dense.py @@ -340,15 +340,15 @@ def find_dense_embedding_for_images(params, opt_tag="inverse_" + timestamp(), op i_1, i_2 = i*BATCH_SIZE, (i+1)*BATCH_SIZE yield sample_latents[i_1:i_2] latent_gen = sample_latent_gen() - TOTAL_IMGS = NUM_IMGS - while TOTAL_IMGS % BATCH_SIZE != 0: + INFILL_IMGS = NUM_IMGS + while INFILL_IMGS % BATCH_SIZE != 0: REMAINDER = 1 # BATCH_SIZE - (NUM_IMGS % BATCH_SIZE) - TOTAL_IMGS += REMAINDER + INFILL_IMGS += REMAINDER sample_images = np.append(sample_images, sample_images[-REMAINDER:,...], axis=0) sample_labels = np.append(sample_labels, sample_labels[-REMAINDER:,...], axis=0) sample_latents = np.append(sample_latents, sample_latents[-REMAINDER:,...], axis=0) sample_fns = np.append(sample_fns, sample_fns[-REMAINDER:], axis=0) - assert(NUM_IMGS % BATCH_SIZE == 0) + assert(INFILL_IMGS % BATCH_SIZE == 0) else: sys.exit('Unknown dataset {}.'.format(params.dataset)) |
