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car-detection-bayes
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Glenn Jocher 2019-07-20 19:27:27 +02:00
parent a6877daa41
commit 05139a6bdd
2 changed files with 8 additions and 13 deletions
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20
README.md
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@ -80,23 +80,17 @@ HS**V** Intensity | +/- 50%
https://cloud.google.com/deep-learning-vm/ https://cloud.google.com/deep-learning-vm/
**Machine type:** n1-standard-8 (8 vCPUs, 30 GB memory) **Machine type:** n1-standard-8 (8 vCPUs, 30 GB memory)
**CPU platform:** Intel Skylake **CPU platform:** Intel Skylake
**GPUs:** K80 ($0.198/hr), P4 ($0.279/hr), T4 ($0.353/hr), P100 ($0.493/hr), V100 ($0.803/hr) **GPUs:** K80 ($0.20/hr), T4 ($0.35/hr), V100 ($0.80/hr) CUDA with Nvidia Apex FP16/32
**HDD:** 100 GB SSD **HDD:** 100 GB SSD
**Dataset:** COCO train 2014 **Dataset:** COCO train 2014 (117,263 images)
GPUs | `batch_size` | batch time | epoch time | epoch cost GPUs | `batch_size` | batch time | epoch time | epoch cost
--- |---| --- | --- | --- --- |---| --- | --- | ---
<i></i> | (images) | (s/batch) | | 1 K80 | 64 (32x2) | 2.9s | 175min | $0.58
1 K80 | 16 | 1.43s | 175min | $0.58 1 T4 | 64 (32x2) | 0.8s | 49min | $0.29
1 P4 | 8 | 0.51s | 125min | $0.58 1 2080ti | 64 (32x2) | - | - | -
1 T4 | 16 | 0.78s | 94min | $0.55 1 V100 | 64 (32x2) | 0.38s | 23min | $0.31
1 P100 | 16 | 0.39s | 48min | $0.39 2 V100 | 64 (64x1) | 0.38s | 23min | $0.62
2 P100 | 32 | 0.48s | 29min | $0.47
4 P100 | 64 | 0.65s | 20min | $0.65
1 V100 | 16 | 0.25s | 31min | $0.41
2 V100 | 32 | 0.29s | 18min | $0.48
4 V100 | 64 | 0.41s | 13min | $0.70
8 V100 | 128 | 0.49s | 7min | $0.80
# Inference # Inference

1
utils/utils.py
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@ -628,6 +628,7 @@ def plot_images(imgs, targets, paths=None, fname='images.jpg'):
fig = plt.figure(figsize=(10, 10)) fig = plt.figure(figsize=(10, 10))
bs, _, h, w = imgs.shape # batch size, _, height, width bs, _, h, w = imgs.shape # batch size, _, height, width
bs = min(bs, 16) # limit plot to 16 images
ns = np.ceil(bs ** 0.5) # number of subplots ns = np.ceil(bs ** 0.5) # number of subplots
for i in range(bs): for i in range(bs):