chrisjay commited on
Commit
4db7f81
1 Parent(s): 35ee063

design edits to space

Browse files
Files changed (6) hide show
  1. app.py +12 -7
  2. data_mnist +1 -1
  3. metrics.json +1 -1
  4. model.pth +1 -1
  5. optimizer.pth +1 -1
  6. utils.py +1 -3
app.py CHANGED
@@ -120,8 +120,8 @@ class MNISTCorrupted(Dataset):
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  self.transform = transform
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  corrupted_dir="./mnist_c"
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  files = [f.name for f in os.scandir(corrupted_dir)]
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- images = [np.load(os.path.join(os.path.join(corrupted_dir,f),'test_images.npy')) for f in files]
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- labels = [np.load(os.path.join(os.path.join(corrupted_dir,f),'test_labels.npy')) for f in files]
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  self.data = np.vstack(images)
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  self.labels = np.hstack(labels)
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@@ -423,13 +423,18 @@ def main():
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  image_input =gr.inputs.Image(source="canvas",shape=(28,28),invert_colors=True,image_mode="L",type="pil")
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- label_output = gr.outputs.Label(num_top_classes=10)
 
 
 
 
 
 
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- submit = gr.Button("Submit")
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- gr.Markdown(MODEL_IS_WRONG)
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- number_dropdown = gr.Dropdown(choices=[i for i in range(10)],type='value',default=None,label="What was the correct prediction?")
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- flag_btn = gr.Button("Flag")
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  output_result = gr.outputs.HTML()
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  adversarial_number = gr.Variable(value=0)
 
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  self.transform = transform
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  corrupted_dir="./mnist_c"
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  files = [f.name for f in os.scandir(corrupted_dir)]
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+ images = [np.load(os.path.join(os.path.join(corrupted_dir,f),'test_images.npy'))[:200] for f in files]
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+ labels = [np.load(os.path.join(os.path.join(corrupted_dir,f),'test_labels.npy'))[:200] for f in files]
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  self.data = np.vstack(images)
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  self.labels = np.hstack(labels)
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  image_input =gr.inputs.Image(source="canvas",shape=(28,28),invert_colors=True,image_mode="L",type="pil")
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+ gr.Markdown(MODEL_IS_WRONG)
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+
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+ with gr.Row():
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+ label_output = gr.outputs.Label(num_top_classes=2)
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+
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+
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+ number_dropdown = gr.Dropdown(choices=[i for i in range(10)],type='value',default=None,label="What was the correct prediction?")
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+ with gr.Row():
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+ submit = gr.Button("Submit")
 
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+ flag_btn = gr.Button("Flag")
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  output_result = gr.outputs.HTML()
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  adversarial_number = gr.Variable(value=0)
data_mnist CHANGED
@@ -1 +1 @@
1
- Subproject commit c6d1292ac6318c7c44131ca2fb18d37535ae1383
 
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+ Subproject commit 351aced7a740962dd354c05cf67efb1f1652739f
metrics.json CHANGED
@@ -1 +1 @@
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- {"all": [10.55875015258789], "0": [0.0], "1": [0.0], "2": [0.0], "3": [43.33333206176758], "4": [86.66666412353516], "5": [0.0], "6": [0.0], "7": [0.0], "8": [0.0], "9": [0.0]}
 
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+ {"all": [10.55875015258789], "0": [0.0, 0.0], "1": [0.0, 0.0], "2": [0.0, 0.0], "3": [43.33333206176758, 100.0], "4": [86.66666412353516, 0.0], "5": [0.0, 0.0], "6": [0.0, 0.0], "7": [0.0, 0.0], "8": [0.0, 0.0], "9": [0.0, 0.0]}
model.pth CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:0615455222f0654123d29490ed6fa00db335abb7bc856a817ed8069c03cfaf42
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  size 89871
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:e6fb83a68fe8dca1a7a9bc9db3029071edaf292ab2c3fda48ac3661579efe873
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  size 89871
optimizer.pth CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:9cfa224990c352a3ad53a41d439d5dd790358bb1e0acb9d3d63379f5c9d0ba7e
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  size 89807
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:29d01887c93ca1c9b69aee6ceb2f77c3c0db91936d5c13e92d5dfc7075bb2237
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  size 89807
utils.py CHANGED
@@ -20,9 +20,7 @@ WHAT_TO_DO="""
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  """
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  MODEL_IS_WRONG = """
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- ---
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-
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- ### Did the model get it wrong? Choose the correct prediction below and flag it. When you flag it, the instance is saved to our dataset and the model is trained on it.
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  """
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  DEFAULT_TEST_METRIC = "<html> Current test metric - Avg. loss: 1000, Accuracy: 30/1000 (30%) </html>"
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  """
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  MODEL_IS_WRONG = """
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+ ### Did the model get it wrong or has a low confidence? Choose the correct prediction below and flag it. When you flag it, the instance is saved to our dataset and the model is trained on it.
 
 
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  """
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  DEFAULT_TEST_METRIC = "<html> Current test metric - Avg. loss: 1000, Accuracy: 30/1000 (30%) </html>"
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