tensor-sensor

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import matplotlib.pyplot as plt
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import numpy as np
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import tsensor
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import torch
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import sys
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W = torch.tensor([[1, 2], [3, 4]], dtype=torch.float32)
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b = torch.tensor([9, 10]).reshape(2, 1)
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x = torch.tensor([4, 5], dtype=torch.int32).reshape(2, 1)
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h = torch.tensor([1,2])
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# fig, ax = plt.subplots(1,1)
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# # view = tsensor.pyviz("b + x", ax=ax, legend=True)
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# # view.savefig("/Users/parrt/Desktop/foo.pdf")
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# plt.show()
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W = torch.rand(size=(2000,2000), dtype=torch.float64)
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b = torch.rand(size=(2000,1), dtype=torch.float64)
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h = torch.zeros(size=(1_000_000,), dtype=int)
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x = torch.rand(size=(2000,1))
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z = torch.rand(size=(2000,1), dtype=torch.complex64)
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g = tsensor.astviz("b = W@b + (h+3).dot(h) + z",
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                   sys._getframe()) # eval, highlight vectors
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g.view()
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# with tsensor.explain():
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#     b + x
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