{IndexError}index 2048 is out of bounds for dimension 1 with size 2048

[zfhxi]

Hello, my test code is as follow:

X1 = torch.randn([10, 2048]).cuda()
X_emb = TorchTSNE(n_components=2, perplexity=100., n_iter=1000).fit_transform(X1)

Sometimes, it will occur '{IndexError}index 2048 is out of bounds for dimension 1 with size 2048', I find the reason is that as 121 line in the tsne_pytorch.py, there may be out of bounds:

119 for i in range(d):
120     if l[i, 1] != 0:
121         M[:, i+1] = M[:, i]
122         i += 1

Concretely, i may equal to d-1 in 121 line which causes M[:,i+1] will be out of bounds(we know M is dxd).

I wonder if the modified code as follow is right?

for i in range(d-1):
    if l[i, 1] != 0:
        M[:, i+1] = M[:, i]
        i += 1

[mxl1990]

Hello, my test code is as follow:

X1 = torch.randn([10, 2048]).cuda()
X_emb = TorchTSNE(n_components=2, perplexity=100., n_iter=1000).fit_transform(X1)

Sometimes, it will occur '{IndexError}index 2048 is out of bounds for dimension 1 with size 2048', I find the reason is that as 121 line in the tsne_pytorch.py, there may be out of bounds:

119 for i in range(d):
120     if l[i, 1] != 0:
121         M[:, i+1] = M[:, i]
122         i += 1

Concretely, i may equal to d-1 in 121 line which causes M[:,i+1] will be out of bounds(we know M is dxd).

I wonder if the modified code as follow is right?

for i in range(d-1):
    if l[i, 1] != 0:
        M[:, i+1] = M[:, i]
        i += 1

rang(d) function do not cover the index d, and d is get from (n, d) = X.shape
so may be something else wrong not here

[zfhxi]

Hello, my test code is as follow:

X1 = torch.randn([10, 2048]).cuda()
X_emb = TorchTSNE(n_components=2, perplexity=100., n_iter=1000).fit_transform(X1)

Sometimes, it will occur '{IndexError}index 2048 is out of bounds for dimension 1 with size 2048', I find the reason is that as 121 line in the tsne_pytorch.py, there may be out of bounds:

119 for i in range(d):
120     if l[i, 1] != 0:
121         M[:, i+1] = M[:, i]
122         i += 1

Concretely, i may equal to d-1 in 121 line which causes M[:,i+1] will be out of bounds(we know M is dxd).
I wonder if the modified code as follow is right?

for i in range(d-1):
    if l[i, 1] != 0:
        M[:, i+1] = M[:, i]
        i += 1

rang(d) function do not cover the index d, and d is get from (n, d) = X.shape so may be something else wrong not here

You are right, but i may equal to d-1, then M[:,i+1] actually is M[:,d] which will occur errors.

[mxl1990]

Hello, my test code is as follow:

X1 = torch.randn([10, 2048]).cuda()
X_emb = TorchTSNE(n_components=2, perplexity=100., n_iter=1000).fit_transform(X1)

Sometimes, it will occur '{IndexError}index 2048 is out of bounds for dimension 1 with size 2048', I find the reason is that as 121 line in the tsne_pytorch.py, there may be out of bounds:

119 for i in range(d):
120     if l[i, 1] != 0:
121         M[:, i+1] = M[:, i]
122         i += 1

Concretely, i may equal to d-1 in 121 line which causes M[:,i+1] will be out of bounds(we know M is dxd).
I wonder if the modified code as follow is right?

for i in range(d-1):
    if l[i, 1] != 0:
        M[:, i+1] = M[:, i]
        i += 1

rang(d) function do not cover the index d, and d is get from (n, d) = X.shape so may be something else wrong not here

You are right, but i may equal to d-1, then M[:,i+1] actually is M[:,d] which will occur errors.

I got it. The matrix M is a dxd matrix which contains n eigenvectors in X.t() * X matrix
I changed the iteration function to avoid this error, thank you for your reminder