write json params

2 files changed, 100 insertions, 3 deletions

diff --git a/cli/app/commands/biggan/search.py b/cli/app/commands/biggan/search.py
index 0b31a0d..5844855 100644
--- a/cli/app/commands/biggan/search.py
+++ b/cli/app/commands/biggan/search.py
@@ -17,6 +17,7 @@ import tensorflow_hub as hub
 import shutil
 import h5py
 
+from app.search.json import save_params_latent, save_params_dense
 from app.search.image import image_to_uint8, imconvert_uint8, imconvert_float32, \
   imread, imwrite, imgrid
 from app.search.vector import truncated_z_sample, truncated_z_single, create_labels
@@ -28,11 +29,13 @@ from app.search.vector import truncated_z_sample, truncated_z_single, create_lab
   help='Dimensions of BigGAN network (128, 256, 512)')
 @click.option('-v', '--video', 'opt_video', is_flag=True,
   help='Export a video for each dataset')
+@click.option('-t', '--tag', 'opt_tag', default='inverse_' + int(time.time() * 1000), 
+  help='Tag this dataset')
 # @click.option('-r', '--recursive', 'opt_recursive', is_flag=True)
 @click.pass_context
 def cli(ctx, opt_fp_in, opt_dims, opt_video):
   """
-  Search for an image in BigGAN using gradient descent
+  Search for an image (class vector) in BigGAN using gradient descent
   """
   generator = hub.Module('https://tfhub.dev/deepmind/biggan-' + str(opt_dims) + '/2')
 
@@ -56,9 +59,11 @@ def cli(ctx, opt_fp_in, opt_dims, opt_video):
   else:
     paths = [opt_fp_in]
 
-  fp_inverses = os.path.join(app_cfg.INVERSES_DIR, 'inverse_' + int(time.time() * 1000))
+  fp_inverses = os.path.join(app_cfg.INVERSES_DIR, opt_tag)
   os.makedirs(fp_inverses, exist_ok=True)
-  out_file = h5py.File(fp_inverses, 'w')
+  save_params_latent(fp_inverses, opt_tag)
+  save_params_dense(fp_inverses, opt_tag)
+  out_file = h5py.File(join(fp_inverses, 'dataset.hdf5'), 'w')
   out_images = out_file.create_dataset('xtrain', (len(paths), 3, 512, 512,), dtype='float32')
   out_labels = out_file.create_dataset('ytrain', (len(paths), vocab_size,), dtype='float32')
 
diff --git a/cli/app/search/json.py b/cli/app/search/json.py
new file mode 100644
index 0000000..0f6c71c
--- /dev/null
+++ b/cli/app/search/json.py
@@ -0,0 +1,92 @@
+from os.path import join
+from app.utils.file_utils import write_json
+
+def save_params_latent(fp_out_dir, tag):
+  data = {
+    "tag": tag,
+    "decay_n": 2, 
+    "features": True, 
+    "clip": 1.0, 
+    "stochastic_clipping": False, 
+    "clipping": False, 
+    "dataset": "inverses/{}/dataset.hdf5".format(tag),
+    "inv_layer": "latent", 
+    "decay_lr": True, 
+    "inv_it": 15000, 
+    "generator_path": "https://tfhub.dev/deepmind/biggan-512/2", 
+    "attention_map_layer": "Generator_2/attention/Softmax:0",
+    "pre_trained_latent": False, 
+    "lambda_dist": 0.0, 
+    "likeli_loss": True, 
+    "init_hi": 0.001, 
+    "lr": 0.1, 
+    "norm_loss": False, 
+    "generator_fixed_inputs": {
+      "truncation": 1.0
+    }, 
+    "log_z_norm": True, 
+    "feature_extractor_path": "https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1", 
+    "mse": True, 
+    "custom_grad_relu": False, 
+    "random_label": False, 
+    "lambda_feat": 1.0, 
+    "init_gen_dist": False, 
+    "log_activation_layer": "Generator_2/GBlock/Relu:0", 
+    "batch_size": 4, 
+    "fixed_z": False, 
+    "feature_extractor_output": "InceptionV3/Mixed_7a", 
+    "init_lo": -0.001, 
+    "lambda_mse": 1.0, 
+    "lambda_reg": 0.1, 
+    "dist_loss": False, 
+    "sample_size": 4, 
+    "dataset": "inverses/{}/dataset.encodings.hdf5".format(tag),
+    "save_progress": True,
+  }
+  fp_out_fn = join(fp_out_dir, "params_latent.json")
+  write_json(data, fp_out_fn)
+
+def save_params_dense(fp_out_dir, tag):
+  data = {
+    "tag": tag,
+    "decay_n": 2, 
+    "features": True, 
+    "clip": 1.0, 
+    "stochastic_clipping": False, 
+    "clipping": False, 
+    "dataset": "inverses/{}/dataset.encodings.hdf5".format(tag),
+    "inv_layer": "Generator_2/G_Z/Reshape:0", 
+    "decay_lr": True, 
+    "inv_it": 15000, 
+    "generator_path": "https://tfhub.dev/deepmind/biggan-512/2", 
+    "attention_map_layer": "Generator_2/attention/Softmax:0",
+    "pre_trained_latent": True, 
+    "lambda_dist": 10.0, 
+    "likeli_loss": False, 
+    "init_hi": 0.001, 
+    "lr": 0.01, 
+    "norm_loss": False, 
+    "generator_fixed_inputs": {
+      "truncation": 1.0
+    }, 
+    "log_z_norm": False, 
+    "feature_extractor_path": "https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1", 
+    "mse": True, 
+    "custom_grad_relu": False, 
+    "random_label": False, 
+    "lambda_feat": 1.0, 
+    "init_gen_dist": False, 
+    "log_activation_layer": "Generator_2/GBlock/Relu:0", 
+    "batch_size": 4, 
+    "fixed_z": True, 
+    "feature_extractor_output": "InceptionV3/Mixed_7a", 
+    "init_lo": -0.001, 
+    "lambda_mse": 1.0, 
+    "lambda_reg": 0.1, 
+    "dist_loss": True, 
+    "sample_size": 4, 
+    "dataset": "inverses/{}/dataset.encodings.dense.hdf5".format(tag),
+    "save_progress": True,
+  }
+  fp_out_fn = join(fp_out_dir, "params_dense.json")
+  write_json(data, fp_out_fn)