diff --git a/tutorial-contents-notebooks/201_torch_numpy.ipynb b/tutorial-contents-notebooks/201_torch_numpy.ipynb index ecf445a..82fbfe6 100644 --- a/tutorial-contents-notebooks/201_torch_numpy.ipynb +++ b/tutorial-contents-notebooks/201_torch_numpy.ipynb @@ -37,16 +37,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "numpy array: [[0 1 2]\n", - " [3 4 5]] \n", - "torch tensor: \n", - " 0 1 2\n", - " 3 4 5\n", - "[torch.LongTensor of size 2x3]\n", - " \n", - "tensor to array: [[0 1 2]\n", - " [3 4 5]]\n" + "\nnumpy array: [[0 1 2]\n [3 4 5]] \ntorch tensor: tensor([[ 0, 1, 2],\n [ 3, 4, 5]], dtype=torch.int32) \ntensor to array: [[0 1 2]\n [3 4 5]]\n" ] } ], @@ -71,16 +62,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "abs \n", - "numpy: [1 2 1 2] \n", - "torch: \n", - " 1\n", - " 2\n", - " 1\n", - " 2\n", - "[torch.FloatTensor of size 4]\n", - "\n" + "\nabs \nnumpy: [1 2 1 2] \ntorch: tensor([ 1., 2., 1., 2.])\n" ] } ], @@ -103,12 +85,7 @@ { "data": { "text/plain": [ - "\n", - " 1\n", - " 2\n", - " 1\n", - " 2\n", - "[torch.FloatTensor of size 4]" + "tensor([ 1., 2., 1., 2.])" ] }, "execution_count": 4, @@ -129,16 +106,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "sin \n", - "numpy: [-0.84147098 -0.90929743 0.84147098 0.90929743] \n", - "torch: \n", - "-0.8415\n", - "-0.9093\n", - " 0.8415\n", - " 0.9093\n", - "[torch.FloatTensor of size 4]\n", - "\n" + "\nsin \nnumpy: [-0.84147098 -0.90929743 0.84147098 0.90929743] \ntorch: tensor([-0.8415, -0.9093, 0.8415, 0.9093])\n" ] } ], @@ -159,12 +127,7 @@ { "data": { "text/plain": [ - "\n", - " 0.2689\n", - " 0.1192\n", - " 0.7311\n", - " 0.8808\n", - "[torch.FloatTensor of size 4]" + "tensor([ 0.2689, 0.1192, 0.7311, 0.8808])" ] }, "execution_count": 6, @@ -184,12 +147,7 @@ { "data": { "text/plain": [ - "\n", - " 0.3679\n", - " 0.1353\n", - " 2.7183\n", - " 7.3891\n", - "[torch.FloatTensor of size 4]" + "tensor([ 0.3679, 0.1353, 2.7183, 7.3891])" ] }, "execution_count": 7, @@ -210,10 +168,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "mean \n", - "numpy: 0.0 \n", - "torch: 0.0\n" + "\nmean \nnumpy: 0.0 \ntorch: tensor(0.)\n" ] } ], @@ -235,15 +190,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "matrix multiplication (matmul) \n", - "numpy: [[ 7 10]\n", - " [15 22]] \n", - "torch: \n", - " 7 10\n", - " 15 22\n", - "[torch.FloatTensor of size 2x2]\n", - "\n" + "\nmatrix multiplication (matmul) \nnumpy: [[ 7 10]\n [15 22]] \ntorch: tensor([[ 7., 10.],\n [ 15., 22.]])\n" ] } ], @@ -300,19 +247,16 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "\n", - " 7 10\n", - " 15 22\n", - "[torch.FloatTensor of size 2x2]" + "tensor([[ 7., 10.],\n [ 15., 22.]])" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -323,19 +267,16 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "\n", - " 1 4\n", - " 9 16\n", - "[torch.FloatTensor of size 2x2]" + "tensor([[ 1., 4.],\n [ 9., 16.]])" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -352,7 +293,7 @@ { "data": { "text/plain": [ - "30.0" + "tensor(7.)" ] }, "execution_count": 13, @@ -361,8 +302,7 @@ } ], "source": [ - "torch.dot(torch.Tensor([2, 3]), torch.Tensor([2, 1])) -7.0" + "torch.dot(torch.Tensor([2, 3]), torch.Tensor([2, 1]))" ] }, {