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# asserts convolutions have different parameters before load |
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for conv1, conv2 in zip(conv_params, conv_params2): |
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assert not torch.equal(conv1, conv2) |
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# asserts layers still have different dimensions |
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# asserts layers still have different dimensions |
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for mod1, mod2 in zip(policy.actor.parameters(), policy2.actor.parameters()): |
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if mod1.shape[0] == 12: |
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assert mod2.shape[0] == 10 |
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