Update src/app.py
Browse filesFix columns, hide graph by default
- src/app.py +4 -2
src/app.py
CHANGED
@@ -186,7 +186,8 @@ col1, col2 = st.columns([1,1.3])
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if gpu_vendor == "Apple":
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col.warning("""For M1/M2 Apple chips, PyTorch uses [Metal Performance Shaders (MPS)](https://huggingface.co/docs/accelerate/usage_guides/mps) as backend.\\
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Remember that Apple M1/M2 chips share memory between CPU and GPU.""", icon="⚠️")
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-
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st.write(f"#### [{model_name}](https://huggingface.co/{model_name}) ({custom_ceil(memory_table.iloc[3,0],1):.1f}B)")
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dtypes = memory_table.columns.tolist()[::-1]
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@@ -199,7 +200,8 @@ with col1:
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info = _memory_table[_memory_table['dtype'] == dtype].set_index('Variable')
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show_gpu_info(info, lora_pct, gpu_vendor)
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st.write(memory_table.iloc[[0, 1, 2, 4]])
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-
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extra = ""
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if gpu_vendor == "Apple":
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st.warning("This graph is irrelevant for M1/M2 chips as they can't run in parallel.", icon="⚠️")
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if gpu_vendor == "Apple":
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col.warning("""For M1/M2 Apple chips, PyTorch uses [Metal Performance Shaders (MPS)](https://huggingface.co/docs/accelerate/usage_guides/mps) as backend.\\
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Remember that Apple M1/M2 chips share memory between CPU and GPU.""", icon="⚠️")
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+
_, col, _ = st.columns([1,3,1])
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with col:
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st.write(f"#### [{model_name}](https://huggingface.co/{model_name}) ({custom_ceil(memory_table.iloc[3,0],1):.1f}B)")
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dtypes = memory_table.columns.tolist()[::-1]
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info = _memory_table[_memory_table['dtype'] == dtype].set_index('Variable')
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show_gpu_info(info, lora_pct, gpu_vendor)
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st.write(memory_table.iloc[[0, 1, 2, 4]])
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+
_, col, _ = st.columns([1,3,1])
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with col.expander("Graph", expanded=False):
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extra = ""
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if gpu_vendor == "Apple":
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st.warning("This graph is irrelevant for M1/M2 chips as they can't run in parallel.", icon="⚠️")
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