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SivananthamandGitHub
a869657f25
* Fix python linter Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Format e2e tests Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Format hack, docs Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Add py-fmt target Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Update python lint workflow Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Rebase master Signed-off-by: Sivanantham Chinnaiyan <[email protected]> --------- Signed-off-by: Sivanantham Chinnaiyan <[email protected]>
76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
import sys
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import requests
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import json
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import math
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from matplotlib import pyplot as plt
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import numpy as np
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from aix360.datasets import MNISTDataset
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import time
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from skimage.color import gray2rgb, label2rgb # since the code wants color images
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print("************************************************************")
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print("************************************************************")
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print("************************************************************")
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print("starting query")
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if len(sys.argv) < 3:
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raise Exception("No endpoint specified. ")
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endpoint = sys.argv[1]
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headers = {"Host": sys.argv[2]}
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parameters = {}
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test_num = 1002
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is_file = False
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if len(sys.argv) > 3:
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try:
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test_num = int(sys.argv[3])
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except Exception: # pylint: disable=broad-except
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is_file = True
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if len(sys.argv) > 4:
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try:
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parameters = json.loads(sys.argv[4])
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except Exception: # pylint: disable=broad-except
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raise Exception("Failed to convert to json format. ")
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if is_file:
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inputs = open(sys.argv[2])
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inputs = json.load(inputs)
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actual = "unk"
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else:
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data = MNISTDataset()
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inputs = data.test_data[test_num]
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labels = data.test_labels[test_num]
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actual = 0
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for x in range(1, len(labels)):
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if labels[x] != 0:
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actual = x
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inputs = gray2rgb(inputs.reshape((-1, 28, 28)))
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inputs = np.reshape(inputs, (28, 28, 3))
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input_image = {"instances": [inputs.tolist()]}
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input_image.update(parameters)
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print("Sending Explain Query")
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x = time.time()
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res = requests.post(endpoint, json=input_image, headers=headers)
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print("TIME TAKEN: ", time.time() - x)
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print(res)
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if not res.ok:
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res.raise_for_status()
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res_json = res.json()
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temp = np.array(res_json["explanations"]["temp"])
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masks = np.array(res_json["explanations"]["masks"])
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top_labels = np.array(res_json["explanations"]["top_labels"])
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fig, m_axs = plt.subplots(math.ceil(len(top_labels) / 5), 5, figsize=(12, 6))
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for i, c_ax in enumerate(m_axs.flatten()):
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if i >= len(top_labels):
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c_ax.axis("off")
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continue
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mask = masks[i]
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c_ax.imshow(label2rgb(mask, temp, bg_label=0), interpolation="nearest")
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c_ax.set_title("Positive for {}\nActual {}".format(top_labels[i], actual))
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c_ax.axis("off")
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plt.show()
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