Spaces:
Running
on
Zero
Running
on
Zero
update gpu
Browse files
app.py
CHANGED
@@ -555,7 +555,7 @@ def compute_ncut(
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affinity_focal_gamma=affinity_focal_gamma,
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knn=knn_ncut,
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).fit_transform(features.reshape(-1, features.shape[-1]))
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-
print(f"NCUT time
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start = time.time()
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if embedding_method == "UMAP":
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@@ -564,7 +564,7 @@ def compute_ncut(
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n_neighbors=n_neighbors,
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min_dist=min_dist,
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)
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-
print(f"UMAP time
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elif embedding_method == "t-SNE":
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X_3d, rgb = rgb_from_tsne_3d(
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eigvecs,
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@@ -572,7 +572,7 @@ def compute_ncut(
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perplexity=perplexity,
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knn=knn_tsne,
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)
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-
print(f"t-SNE time
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else:
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raise ValueError(f"Embedding method {embedding_method} not supported.")
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@@ -657,7 +657,7 @@ demo = gr.Interface(
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additional_inputs=[
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gr.Dropdown(["attn", "mlp", "block"], label="Node type", value="block", elem_id="node_type", info="attn: attention output, mlp: mlp output, block: sum of residual stream"),
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gr.Slider(0.01, 1, step=0.01, label="Affinity focal gamma", value=0.3, elem_id="affinity_focal_gamma", info="decrease for more aggressive cleaning on the affinity matrix"),
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-
gr.Slider(100,
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gr.Slider(1, 100, step=1, label="KNN (NCUT)", value=10, elem_id="knn_ncut", info="for Nyström approximation"),
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gr.Dropdown(["t-SNE", "UMAP"], label="Embedding method", value="t-SNE", elem_id="embedding_method"),
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gr.Slider(100, 1000, step=100, label="num_sample (t-SNE/UMAP)", value=300, elem_id="num_sample_tsne", info="for Nyström approximation. Adding will slow down quite a lot"),
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affinity_focal_gamma=affinity_focal_gamma,
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knn=knn_ncut,
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).fit_transform(features.reshape(-1, features.shape[-1]))
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+
print(f"NCUT time: {time.time() - start:.2f}s")
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start = time.time()
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if embedding_method == "UMAP":
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n_neighbors=n_neighbors,
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min_dist=min_dist,
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)
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+
print(f"UMAP time: {time.time() - start:.2f}s")
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elif embedding_method == "t-SNE":
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X_3d, rgb = rgb_from_tsne_3d(
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eigvecs,
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perplexity=perplexity,
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knn=knn_tsne,
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)
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+
print(f"t-SNE time: {time.time() - start:.2f}s")
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else:
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raise ValueError(f"Embedding method {embedding_method} not supported.")
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additional_inputs=[
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gr.Dropdown(["attn", "mlp", "block"], label="Node type", value="block", elem_id="node_type", info="attn: attention output, mlp: mlp output, block: sum of residual stream"),
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gr.Slider(0.01, 1, step=0.01, label="Affinity focal gamma", value=0.3, elem_id="affinity_focal_gamma", info="decrease for more aggressive cleaning on the affinity matrix"),
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+
gr.Slider(100, 50000, step=100, label="num_sample (NCUT)", value=25000, elem_id="num_sample_ncut", info="for Nyström approximation"),
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gr.Slider(1, 100, step=1, label="KNN (NCUT)", value=10, elem_id="knn_ncut", info="for Nyström approximation"),
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gr.Dropdown(["t-SNE", "UMAP"], label="Embedding method", value="t-SNE", elem_id="embedding_method"),
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gr.Slider(100, 1000, step=100, label="num_sample (t-SNE/UMAP)", value=300, elem_id="num_sample_tsne", info="for Nyström approximation. Adding will slow down quite a lot"),
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