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-rw-r--r--cli/app/search/search_dense.py21
1 files changed, 8 insertions, 13 deletions
diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py
index 392fa70..a538d0d 100644
--- a/cli/app/search/search_dense.py
+++ b/cli/app/search/search_dense.py
@@ -72,15 +72,13 @@ def find_dense_embedding_for_images(params):
LATENT_TAG = 'latent' if params.inv_layer == 'latent' else 'dense'
BATCH_SIZE = params.batch_size
SAMPLE_SIZE = params.sample_size
- LOGS_DIR = os.path.join('inverses', params.tag, LATENT_TAG, 'logs')
- SAMPLES_DIR = os.path.join('inverses', params.tag, LATENT_TAG, 'samples')
- INVERSES_DIR = os.path.join('inverses', params.tag)
- if not os.path.exists(LOGS_DIR):
- os.makedirs(LOGS_DIR)
- if not os.path.exists(SAMPLES_DIR):
- os.makedirs(SAMPLES_DIR)
- if not os.path.exists(INVERSES_DIR):
- os.makedirs(INVERSES_DIR)
+ LOGS_DIR = os.path.join(params.path, LATENT_TAG, 'logs')
+ SAMPLES_DIR = os.path.join(params.path, LATENT_TAG, 'samples')
+ VECTOR_DIR = os.path.join(params.path, 'vectors')
+
+ os.makedirs(LOGS_DIR, exist_ok=True)
+ os.makedirs(SAMPLES_DIR, exist_ok=True)
+ os.makedirs(VECTOR_DIR, exist_ok=True)
# --------------------------
# Util functions.
@@ -410,7 +408,7 @@ def find_dense_embedding_for_images(params):
NUM_IMGS_TO_PROCESS = NUM_IMGS
# Output file.
- out_file = h5py.File(os.path.join(INVERSES_DIR, params.out_dataset), 'w')
+ out_file = h5py.File(params.out_dataset, 'w')
out_images = out_file.create_dataset('xtrain', [NUM_IMGS_TO_PROCESS,] + IMG_SHAPE, dtype='float32')
out_enc = out_file.create_dataset('encoding', [NUM_IMGS_TO_PROCESS,] + ENC_SHAPE, dtype='float32')
out_lat = out_file.create_dataset('latent', [NUM_IMGS_TO_PROCESS, Z_DIM], dtype='float32')
@@ -421,9 +419,6 @@ def find_dense_embedding_for_images(params):
out_fns[:] = sample_fns[:NUM_IMGS_TO_PROCESS]
- vector_dir = os.path.join(app_cfg.INVERSES_DIR, "vectors")
- os.makedirs(vector_dir, exist_ok=True)
-
# Gradient descent w.r.t. generator's inputs.
it = 0
out_pos = 0