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{ | |
"$schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentTemplate.json#", | |
"contentVersion": "1.0.0.0", | |
"parameters": { | |
"hostingPlanName": { | |
"type": "string", | |
"minLength": 1, | |
"metadata": { | |
"description": "Name of the hosting plan to use in Azure." | |
} |
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MI_dir_L5_weight | MI_dir_L5_mean | MI_dir_L5_variance | MI_dir_L3_weight | MI_dir_L3_mean | MI_dir_L3_variance | MI_dir_L1_weight | MI_dir_L1_mean | MI_dir_L1_variance | MI_dir_L0.1_weight | MI_dir_L0.1_mean | MI_dir_L0.1_variance | MI_dir_L0.01_weight | MI_dir_L0.01_mean | MI_dir_L0.01_variance | H_L5_weight | H_L5_mean | H_L5_variance | H_L3_weight | H_L3_mean | H_L3_variance | H_L1_weight | H_L1_mean | H_L1_variance | H_L0.1_weight | H_L0.1_mean | H_L0.1_variance | H_L0.01_weight | H_L0.01_mean | H_L0.01_variance | HH_L5_weight | HH_L5_mean | HH_L5_std | HH_L5_magnitude | HH_L5_radius | HH_L5_covariance | HH_L5_pcc | HH_L3_weight | HH_L3_mean | HH_L3_std | HH_L3_magnitude | HH_L3_radius | HH_L3_covariance | HH_L3_pcc | HH_L1_weight | HH_L1_mean | HH_L1_std | HH_L1_magnitude | HH_L1_radius | HH_L1_covariance | HH_L1_pcc | HH_L0.1_weight | HH_L0.1_mean | HH_L0.1_std | HH_L0.1_magnitude | HH_L0.1_radius | HH_L0.1_covariance | HH_L0.1_pcc | HH_L0.01_weight | HH_L0.01_mean | HH_L0.01_std | HH_L0.01_magnitude | HH_L0.01_radius | HH_L0.01_covariance | HH_L0.01_pcc | HH_jit_L5_weight | HH_jit_L5_mean | HH_jit_L5_variance | HH_jit_L3_weight | HH_jit |
---|
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import os | |
import random | |
import numpy as np | |
from tqdm import tqdm | |
from omegaconf import DictConfig | |
import torch | |
import torch.nn as nn | |
import torch.backends.cudnn as cudnn |
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import torch | |
def format_pytorch_version(version): | |
return version.split('+')[0] | |
TORCH_version = torch.__version__ | |
TORCH = format_pytorch_version(TORCH_version) | |
def format_cuda_version(version): | |
return 'cu' + version.replace('.', '') |
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I0805 09:46:50.326969 140593525006912 xla_bridge.py:328] Unable to initialize backend 'tpu_driver': NOT_FOUND: Unable to find driver in registry given worker: | |
I0805 09:46:50.384492 140593525006912 xla_bridge.py:328] Unable to initialize backend 'rocm': NOT_FOUND: Could not find registered platform with name: "rocm". Available platform names are: CUDA Host Interpreter | |
I0805 09:46:50.385140 140593525006912 xla_bridge.py:328] Unable to initialize backend 'tpu': module 'jaxlib.xla_extension' has no attribute 'get_tpu_client' | |
I0805 09:46:50.385412 140593525006912 main.py:68] JAX host: 0 / 1 | |
I0805 09:46:50.385540 140593525006912 main.py:69] JAX devices: [GpuDevice(id=0, process_index=0), GpuDevice(id=1, process_index=0), GpuDevice(id=2, process_index=0), GpuDevice(id=3, process_index=0)] | |
I0805 09:46:50.918455 140593525006912 dataset_info.py:365] Load dataset info from /nfs/users/ext_vishal.thengane/tensorflow_datasets/cifar100/3.0.2 | |
I0805 09:46:50.923666 140593525006912 dataset_builder.py:351] Reusing dataset cifa |
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import ruamel.yaml | |
yaml = ruamel.yaml.YAML() | |
data = yaml.load(open('environment.yml')) | |
requirements = [] | |
for dep in data['dependencies']: | |
if isinstance(dep, str): | |
package, package_version, python_version = dep.split('=') | |
if python_version == '0': |
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# Byte-compiled / optimized / DLL files | |
__pycache__/ | |
*.py[cod] | |
*$py.class | |
# C extensions | |
*.so | |
# Distribution / packaging | |
.Python |
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import streamlit as st | |
from streamlit.hashing import _CodeHasher | |
try: | |
# Before Streamlit 0.65 | |
from streamlit.ReportThread import get_report_ctx | |
from streamlit.server.Server import Server | |
except ModuleNotFoundError: | |
# After Streamlit 0.65 | |
from streamlit.report_thread import get_report_ctx |