Review all code up to this point #4
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generate embedding torch.tensor numpy warning
meherkasam
requested review from
tarunn2799,
ajaykrishnan23,
subhiksha-m and
M-I-Dx
| """ | ||
| if name == "gaussian": | ||
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| def gaussian(x, mean, sigma): |
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I'd recommend refactoring this into a separate class, perhaps called GaussianStrategy.
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Similarly with other strategies.
| def gaussian(x, mean, sigma): | ||
| a = 1 / (sigma * np.sqrt(2 * np.pi)) | ||
| exp_val = -(1 / 2) * (((x - mean) ** 2) / (sigma ** 2)) | ||
| tmp = list(a * np.exp(exp_val))[0] |
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Consider using result rather than tmp.
| sigma = 0.2 | ||
| return [gaussian(conf_i, mean, sigma) for conf_i in confidences] | ||
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| def get_samples(image_list, confidences, number_of_samples): |
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Nitpick: number_of_samples could be renamed as sample_count to avoid the need for a preposition.
| ) | ||
| return picked_samples | ||
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| def get_index(samples, dataset): |
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The function is called get_index, but the result appears to be an element in dataset.
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| def get_index(samples, dataset): | ||
| data_index = [] | ||
| for i in samples: |
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You could use the map function in place of this for loop as follows:
data_index = map(lambda x: dataset.index(x), samples)
| super().__init__() | ||
| """ | ||
| Keyword arguments | ||
| n_input -- Size of the input embeddings |
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Hungarian notation is typically discouraged for variable naming. Consider changing these to input_size, num_classes or class_count, etc.
| class SSLEvaluator(nn.Module): | ||
| """The classification model which is used with the SSL encoder""" | ||
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| def __init__(self, n_input, n_classes, n_hidden=512, p=0.1, c_type="Sigmoid"): |
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Might be worthwhile making classification type into an enum.
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| import torch | |||
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Consider maintaining a consistent folder and file naming structure. Typically in Python, file and folder names are all lowercase and underscores are used to separate words.
| class SimCLRTransform(Pipeline): | ||
| def __init__( | ||
| self, | ||
| DATA_PATH, |
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All caps should ideally only be used for constants.
References:
PEP8
Python naming convention
| image = self.swapaxes(image) | ||
| return image | ||
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| def define_graph(self): |
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This function returns a batch. Would be helpful to have the name of the function be more descriptive of what it returns.
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