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@ -23,7 +23,7 @@ def forward(model, X, is_train):
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nI = model.get_dim("nI")
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W = model.get_param("W")
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# Preallocate array for layer output, including padding.
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Yf = model.ops.alloc2f(X.shape[0] + 1, nF * nO * nP, zeros=False)
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Yf = model.ops.alloc2f(X.shape[0] + 1, nF * nO * nP, zeros=False)
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model.ops.gemm(X, W.reshape((nF * nO * nP, nI)), trans2=True, out=Yf[1:])
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Yf = Yf.reshape((Yf.shape[0], nF, nO, nP))
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Yf[0] = model.get_param("pad")
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