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Replace progressbar with tqdm #3494

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Nov 16, 2024
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Replace progressbar with tqdm #3494

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26 changes: 10 additions & 16 deletions Examples/onnx/utils/image_net_evaluator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,7 @@
"""
import logging

import progressbar
from tqdm import tqdm
import torch
import onnxruntime as ort

Expand Down Expand Up @@ -92,25 +92,19 @@ def evaluate(self, sess: ort.InferenceSession, iterations: int = None) -> float:
logger.info("Evaluating nn.Module for %d iterations with batch_size %d",
iterations, self._val_data_loader.batch_size)

batch_cntr = 1
with progressbar.ProgressBar(max_value=iterations) as progress_bar:
for input_data, target_data in self._val_data_loader:
for i, (input_data, target_data) in tqdm(enumerate(self._val_data_loader), total=10):
if i == 10:
break

inputs_batch = input_data.numpy()
inputs_batch = input_data.numpy()

predicted_batch = sess.run(None, {input_name : inputs_batch})[0]
predicted_batch = sess.run(None, {input_name : inputs_batch})[0]

batch_avg_top_1_5 = accuracy(output=torch.from_numpy(predicted_batch), target=target_data,
topk=(1, 5))
batch_avg_top_1_5 = accuracy(output=torch.from_numpy(predicted_batch), target=target_data,
topk=(1, 5))

acc_top1 += batch_avg_top_1_5[0].item()
acc_top5 += batch_avg_top_1_5[1].item()

progress_bar.update(batch_cntr)

batch_cntr += 1
if batch_cntr > iterations:
break
acc_top1 += batch_avg_top_1_5[0].item()
acc_top5 += batch_avg_top_1_5[1].item()

acc_top1 /= iterations
acc_top5 /= iterations
Expand Down
18 changes: 8 additions & 10 deletions Examples/torch/quantization/qat_range_learning_ddp_eval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,7 @@
import socket
import argparse

import progressbar
from tqdm import tqdm
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
Expand Down Expand Up @@ -129,15 +129,13 @@ def evaluate_quant(model, _):
model.to(device)
model.eval()

with progressbar.ProgressBar(max_value=100) as progress_bar:
with torch.no_grad():
for i, (images, _) in enumerate(val_loader):
images = images.to(device)
# compute output
_ = model(images)
progress_bar.update(i)
if i == 100:
break
with torch.no_grad():
for i, (images, _) in tqdm(enumerate(val_loader), total=100):
images = images.to(device)
# compute output
_ = model(images)
if i == 100:
break

return evaluate_quant

Expand Down
30 changes: 12 additions & 18 deletions Examples/torch/utils/image_net_evaluator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,7 @@
"""
import logging

import progressbar
from tqdm import tqdm
import torch
from torch import nn

Expand Down Expand Up @@ -104,27 +104,21 @@ def evaluate(self, model: nn.Module, iterations: int = None, use_cuda: bool = Fa
model = model.to(device)
model = model.eval()

batch_cntr = 1
with progressbar.ProgressBar(max_value=iterations) as progress_bar:
with torch.no_grad():
for input_data, target_data in self._val_data_loader:
with torch.no_grad():
for i, (input_data, target_data) in tqdm(enumerate(self._val_data_loader), total=iterations):
if i == iterations:
break

inputs_batch = input_data.to(device)
target_batch = target_data.to(device)
inputs_batch = input_data.to(device)
target_batch = target_data.to(device)

predicted_batch = model(inputs_batch)
predicted_batch = model(inputs_batch)

batch_avg_top_1_5 = accuracy(output=predicted_batch, target=target_batch,
topk=(1, 5))
batch_avg_top_1_5 = accuracy(output=predicted_batch, target=target_batch,
topk=(1, 5))

acc_top1 += batch_avg_top_1_5[0].item()
acc_top5 += batch_avg_top_1_5[1].item()

progress_bar.update(batch_cntr)

batch_cntr += 1
if batch_cntr > iterations:
break
acc_top1 += batch_avg_top_1_5[0].item()
acc_top5 += batch_avg_top_1_5[1].item()

acc_top1 /= iterations
acc_top5 /= iterations
Expand Down
57 changes: 26 additions & 31 deletions Examples/torch/utils/image_net_trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,7 @@
"""
import logging

import progressbar
from tqdm import tqdm
import torch
from torch import nn, optim

Expand Down Expand Up @@ -103,36 +103,31 @@ def _train_loop(self, model: nn.Module, criterion: torch.nn.modules.loss, optimi
model.train()

avg_loss = 0.0
curr_iter = 1

with progressbar.ProgressBar(max_value=max_iterations) as progress_bar:
for images, target in self._train_loader:
images = images.to(device)
target = target.to(device)

# compute model output
output = model(images)
loss = criterion(output, target)
avg_loss += loss.item()

# compute gradient and do SGD step
optimizer.zero_grad()
loss.backward()
optimizer.step()

progress_bar.update(curr_iter)

if curr_iter % debug_steps == 0:
eval_accuracy = self._evaluator.evaluate(model, use_cuda=use_cuda)
logger.info('Epoch #%d/%d: iteration #%d/%d: Global Avg Loss=%f, Eval Accuracy=%f',
current_epoch, max_epochs, curr_iter, max_iterations,
avg_loss / curr_iter, eval_accuracy)
# switch to training mode after evaluation
model.train()

curr_iter += 1
if curr_iter > max_iterations:
break

for i, (images, target) in tqdm(enumerate(self._train_loader), total=max_iterations):
if i == max_iterations:
break

images = images.to(device)
target = target.to(device)

# compute model output
output = model(images)
loss = criterion(output, target)
avg_loss += loss.item()

# compute gradient and do SGD step
optimizer.zero_grad()
loss.backward()
optimizer.step()

if (i+1) % debug_steps == 0:
eval_accuracy = self._evaluator.evaluate(model, use_cuda=use_cuda)
logger.info('Epoch #%d/%d: iteration #%d/%d: Global Avg Loss=%f, Eval Accuracy=%f',
current_epoch, max_epochs, curr_iter, max_iterations,
avg_loss / curr_iter, eval_accuracy)
# switch to training mode after evaluation
model.train()

eval_accuracy = self._evaluator.evaluate(model, use_cuda=use_cuda)
print("eval : ", eval_accuracy)
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.onnx-cpu
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Expand Up @@ -170,7 +170,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.onnx-gpu
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Original file line number Diff line number Diff line change
Expand Up @@ -181,7 +181,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.tf-cpu
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Original file line number Diff line number Diff line change
Expand Up @@ -153,7 +153,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.19.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.tf-gpu
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Expand Up @@ -164,7 +164,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.19.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.tf-torch-cpu
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Expand Up @@ -158,7 +158,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
# protobuf==3.20.1 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.torch-cpu
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Expand Up @@ -169,7 +169,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.torch-cpu-pt113
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Expand Up @@ -169,7 +169,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.torch-gpu
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Expand Up @@ -181,7 +181,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/Dockerfile.torch-gpu-pt113
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Expand Up @@ -181,7 +181,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/fast-release/Dockerfile.torch-gpu-pt21-py310
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Expand Up @@ -178,7 +178,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion Jenkins/fast-release/Dockerfile.torch-gpu-pt21-py38
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Expand Up @@ -174,7 +174,6 @@ RUN python3 -m pip --no-cache-dir install \
piccolo-theme \
Pillow==9.3.0 \
pluggy==0.12.0 \
progressbar2 \
protobuf==3.20.2 \
psutil \
ptflops \
Expand Down
1 change: 0 additions & 1 deletion packaging/dependencies/fast-release/torch-gpu-pt21-py310/reqs_pip_torch_gpu.txt
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Expand Up @@ -15,7 +15,6 @@ onnx==1.14.1
onnxsim
osqp
pandas==1.5.3
progressbar2
protobuf==3.20.2
psutil
pybind11
Expand Down
1 change: 0 additions & 1 deletion packaging/dependencies/fast-release/torch-gpu-pt21-py38/reqs_pip_torch_gpu.txt
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Expand Up @@ -14,7 +14,6 @@ onnx==1.14.1
onnxsim
osqp
pandas==1.5.3
progressbar2
protobuf==3.20.2
psutil
pybind11
Expand Down
1 change: 0 additions & 1 deletion packaging/dependencies/reqs_pip_common.txt
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Expand Up @@ -6,7 +6,6 @@ hvplot==0.9.2
Jinja2==3.0.3
jsonschema
osqp
progressbar2
pybind11
PyYAML
scikit-learn==1.1.3
Expand Down
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