Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
romanbredehoft-zama
commited on
Commit
•
31284a7
1
Parent(s):
a241bb3
Rename Account_length feature to Account_age
Browse files- app.py +2 -2
- backend.py +2 -2
- data/data.csv +1 -1
- deployment_files/client.zip +2 -2
- deployment_files/server.zip +2 -2
- settings.py +2 -2
app.py
CHANGED
@@ -90,7 +90,7 @@ with demo:
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with gr.Column():
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gr.Markdown("### Bank ")
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-
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with gr.Column():
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gr.Markdown("### Third party ")
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@@ -193,7 +193,7 @@ with demo:
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# side to the server
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encrypt_button_bank.click(
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pre_process_encrypt_send_bank,
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-
inputs=[client_id,
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outputs=[encrypted_input_bank],
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)
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with gr.Column():
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gr.Markdown("### Bank ")
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+
account_age = gr.Slider(**ACCOUNT_MIN_MAX, step=1, label="Account age (months)", info="How long have this person had this bank account (in months) ?")
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with gr.Column():
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gr.Markdown("### Third party ")
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# side to the server
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encrypt_button_bank.click(
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pre_process_encrypt_send_bank,
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+
inputs=[client_id, account_age],
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outputs=[encrypted_input_bank],
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)
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backend.py
CHANGED
@@ -290,9 +290,9 @@ def pre_process_encrypt_send_bank(client_id, *inputs):
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(int, bytes): Integer ID representing the current client and a byte short representation of
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the encrypted input to send.
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"""
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-
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-
return _encrypt_send(client_id,
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def pre_process_encrypt_send_third_party(client_id, *inputs):
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(int, bytes): Integer ID representing the current client and a byte short representation of
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the encrypted input to send.
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"""
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+
account_age = inputs[0]
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+
return _encrypt_send(client_id, account_age, "bank")
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def pre_process_encrypt_send_third_party(client_id, *inputs):
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data/data.csv
CHANGED
@@ -1,4 +1,4 @@
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-
Own_car,Own_property,Work_phone,Phone,Email,Salaried,Num_children,Household_size,
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1,1,1,0,0,1,0,2,15,59850.00000000001,32.86857361889703,12.4355736257418,Working,Higher education,Civil marriage,Rented apartment,Other,1
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1,1,0,0,0,1,0,2,29,15750.000000000002,58.79381506807121,3.104786545924968,Working,Secondary / secondary special,Married,House / apartment,Security staff,0
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0,1,0,1,1,1,0,1,4,37800.0,52.32140290355038,8.353354278321937,Commercial associate,Secondary / secondary special,Single / not married,House / apartment,Sales staff,0
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+
Own_car,Own_property,Work_phone,Phone,Email,Salaried,Num_children,Household_size,Account_age,Total_income,Age,Years_employed,Income_type,Education_type,Family_status,Housing_type,Occupation_type,Target
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1,1,1,0,0,1,0,2,15,59850.00000000001,32.86857361889703,12.4355736257418,Working,Higher education,Civil marriage,Rented apartment,Other,1
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1,1,0,0,0,1,0,2,29,15750.000000000002,58.79381506807121,3.104786545924968,Working,Secondary / secondary special,Married,House / apartment,Security staff,0
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0,1,0,1,1,1,0,1,4,37800.0,52.32140290355038,8.353354278321937,Commercial associate,Secondary / secondary special,Single / not married,House / apartment,Sales staff,0
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deployment_files/client.zip
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:b698501c432ade8d406a3d83fcff9a86ed59a4c693116d14b72815602b04b1d9
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+
size 75886
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deployment_files/server.zip
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:73e247b96ac6325fde795f2f6e6c8cd43946b5e5979421845283871bb8e0475e
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+
size 3356
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settings.py
CHANGED
@@ -50,7 +50,7 @@ USER_COLUMNS = [
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'Total_income', 'Age', 'Income_type', 'Education_type', 'Family_status', 'Housing_type',
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'Occupation_type',
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]
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-
BANK_COLUMNS = ["
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THIRD_PARTY_COLUMNS = ["Years_employed", "Salaried"]
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_data = pandas.read_csv(DATA_PATH, encoding="utf-8")
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@@ -63,7 +63,7 @@ def get_min_max(data, column):
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}
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# App data min and max values
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-
ACCOUNT_MIN_MAX = get_min_max(_data, "
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CHILDREN_MIN_MAX = get_min_max(_data, "Num_children")
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INCOME_MIN_MAX = get_min_max(_data, "Total_income")
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AGE_MIN_MAX = get_min_max(_data, "Age")
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'Total_income', 'Age', 'Income_type', 'Education_type', 'Family_status', 'Housing_type',
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'Occupation_type',
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]
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+
BANK_COLUMNS = ["Account_age"]
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THIRD_PARTY_COLUMNS = ["Years_employed", "Salaried"]
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_data = pandas.read_csv(DATA_PATH, encoding="utf-8")
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}
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# App data min and max values
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+
ACCOUNT_MIN_MAX = get_min_max(_data, "Account_age")
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CHILDREN_MIN_MAX = get_min_max(_data, "Num_children")
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INCOME_MIN_MAX = get_min_max(_data, "Total_income")
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AGE_MIN_MAX = get_min_max(_data, "Age")
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