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Running
on
CPU Upgrade
Right column name
Browse files- src/app.py +3 -3
- src/model_utils.py +1 -1
src/app.py
CHANGED
@@ -17,13 +17,13 @@ def get_results(model_name: str, library: str, options: list, access_token: str)
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stages = {"model": [], "gradients": [], "optimizer": [], "step": []}
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for i, option in enumerate(data):
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for stage in stages:
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stages[stage].append(option["Training using Adam"][stage])
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value = max(data[i]["Training using Adam"].values())
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if value == -1:
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value = "N/A"
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else:
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value = convert_bytes(value)
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data[i]["Training using Adam"] = value
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if any(value != -1 for value in stages["model"]):
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out_explain = "## Training using Adam explained:\n"
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stages = {"model": [], "gradients": [], "optimizer": [], "step": []}
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for i, option in enumerate(data):
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for stage in stages:
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+
stages[stage].append(option["Training using Adam (Peek vRAM)"][stage])
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+
value = max(data[i]["Training using Adam (Peek vRAM)"].values())
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if value == -1:
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value = "N/A"
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else:
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value = convert_bytes(value)
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+
data[i]["Training using Adam (Peek vRAM)"] = value
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if any(value != -1 for value in stages["model"]):
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out_explain = "## Training using Adam explained:\n"
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src/model_utils.py
CHANGED
@@ -97,7 +97,7 @@ def calculate_memory(model: torch.nn.Module, options: list):
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"dtype": dtype,
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"Largest Layer or Residual Group": dtype_largest_layer,
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"Total Size": dtype_total_size,
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"Training using Adam": dtype_training_size,
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}
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)
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return data
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"dtype": dtype,
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"Largest Layer or Residual Group": dtype_largest_layer,
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"Total Size": dtype_total_size,
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+
"Training using Adam (Peek vRAM)": dtype_training_size,
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}
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)
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return data
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