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Fix typos.
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tensorflower-gardener authored and Copybara-Service committed Jul 30, 2020
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10 changes: 5 additions & 5 deletions site/en/guide/tensor.ipynb
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"\n",
"If you're familiar with [NumPy](https://numpy.org/devdocs/user/quickstart.html), tensors are (kind of) like `np.arrays`.\n",
"\n",
"All tensors are immutable like python numbers and strings: you can never update the contents of a tensor, only create a new one.\n"
"All tensors are immutable like Python numbers and strings: you can never update the contents of a tensor, only create a new one.\n"
]
},
{
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"source": [
"### Single-axis indexing\n",
"\n",
"TensorFlow follow standard python indexing rules, similar to [indexing a list or a string in python](https://docs.python.org/3/tutorial/introduction.html#strings), and the bacic rules for numpy indexing.\n",
"TensorFlow follows standard Python indexing rules, similar to [indexing a list or a string in Python](https://docs.python.org/3/tutorial/introduction.html#strings), and the basic rules for NumPy indexing.\n",
"\n",
"* indexes start at `0`\n",
"* negative indices count backwards from the end\n",
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"id": "3RLCzAOHjfEH"
},
"source": [
"You can index using any combination integers and slices:"
"You can index using any combination of integers and slices:"
]
},
{
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"id": "gIB2tOkoVr6E"
},
"source": [
"The data maintains it's layout in memory and a new tensor is created, with the requested shape, pointing to the same data. TensorFlow uses C-style \"row-major\" memory ordering, where incrementing the right-most index corresponds to a single step in memory."
"The data maintains its layout in memory and a new tensor is created, with the requested shape, pointing to the same data. TensorFlow uses C-style \"row-major\" memory ordering, where incrementing the rightmost index corresponds to a single step in memory."
]
},
{
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"\n",
"When creating a `tf.Tensor` from a Python object you may optionally specify the datatype.\n",
"\n",
"If you don't, TensorFlow chooses a datatype that can represent your data. TensorFlow converts Python integers to `tf.int32` and python floating point numbers to `tf.float32`. Otherwise TensorFlow uses the same rules NumPy uses when converting to arrays.\n",
"If you don't, TensorFlow chooses a datatype that can represent your data. TensorFlow converts Python integers to `tf.int32` and Python floating point numbers to `tf.float32`. Otherwise TensorFlow uses the same rules NumPy uses when converting to arrays.\n",
"\n",
"You can cast from type to type."
]
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