Spaces:
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Sleeping
Jonas Becker
commited on
Commit
•
46cd050
1
Parent(s):
7f19394
caching model generation
Browse files
app.py
CHANGED
@@ -8,32 +8,33 @@ import transforms as trans
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P_MODEL = "model/drilling_ds_btcvae"
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# GUI -----------------------------------------------------------
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latent_vector = np.array([st.slider(f"L{l}",min_value=-3.0,max_value=3.0,value=0.0) for l in range(3)])
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latent_vector = np.concatenate([latent_vector,np.zeros(7)],axis=0)
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ts = img2ts(value)
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df = pd.DataFrame({
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"x":np.arange(len(ts)),
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@@ -41,10 +42,4 @@ df = pd.DataFrame({
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}
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st.line_chart(df,x="x",y="y")
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st.write(ts)
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# st.write(value)
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# st.image(value, use_column_width="always")
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# x = st.slider("Select a value")
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# st.write(x, "squared is", x * x)
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P_MODEL = "model/drilling_ds_btcvae"
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@st.cache_resource
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def load_decode_function():
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sorter = trans.LatentSorter(disvae.get_kl_dict(P_MODEL))
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vae = disvae.load_model(P_MODEL)
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scaler = trans.MinMaxScaler(_min=torch.tensor([1.3]),_max=torch.tensor([4.0]),min_norm=0.3,max_norm=0.6)
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imaging = trans.SumField()
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_dec = trans.sequential_function(
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sorter.inv,
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vae.decoder,
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scaler.inv,
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imaging.inv
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)
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def decode(latent):
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with torch.no_grad():
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return trans.np_sample(_dec)(latent)
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return decode
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decode = load_decode_function()
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latent_vector = np.array([st.slider(f"L{l}",min_value=-3.0,max_value=3.0,value=0.0) for l in range(3)])
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latent_vector = np.concatenate([latent_vector,np.zeros(7)],axis=0)
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ts = decode(latent_vector)
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df = pd.DataFrame({
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"x":np.arange(len(ts)),
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}
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)
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st.line_chart(df,x="x",y="y")
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