Browse Sebastian Gutierrez's Lessons

showing 92 lessons...

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  PyTorch Autograd: Define A PyTorch Tensor With Autograd

  PyTorch Autograd - Use PyTorch's requires_grad to define a PyTorch Tensor with Autograd

    1:55
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  PyTorch Tensor To List: Convert a PyTorch Tensor To A Python List

  PyTorch Tensor To List: Use PyTorch tolist() to convert a PyTorch Tensor into a Python list

    2:58
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  tf.transpose: Transpose A Matrix in TensorFlow

  tf.transpose - Use TensorFlow's transpose operation to transpose a TensorFlow matrix tensor

    2:23
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  tf.dtype: Print And Check TensorFlow Tensor Type

  tf.dtype - Use TensorFlow's dtype operation to print and check a TensorFlow's Tensor data type

    2:21
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  PyTorch item: Convert A 0-dim PyTorch Tensor To A Python Number

  PyTorch item - Use PyTorch's item operation to convert a 0-dim PyTorch Tensor to a Python number

    1:50
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  PyTorch Min: Get Minimum Value Of A PyTorch Tensor

  PyTorch Min - Use PyTorch's min operation to calculate the min of a PyTorch tensor

    1:55
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  PyTorch Max: Get Maximum Value Of A PyTorch Tensor

  PyTorch Max - Use PyTorch's max operation to calculate the max of a PyTorch tensor

    1:56
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  Print PyTorch Version

  Find out which version of PyTorch is installed in your system by printing the PyTorch version

    0:59
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  PyTorch Matrix Multiplication: How To Do A PyTorch Dot Product

  PyTorch Matrix Multiplication - Use torch.mm to do a PyTorch Dot Product

    3:26
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  tf.reduce_min: Get Minimum Value Of A TensorFlow Tensor

  tf.reduce_min - Use TensorFlow's reduce_min operation to get the minimum value of a TensorFlow Tensor

    1:42
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  tf.random_uniform: Create TensorFlow Tensor With Random Uniform Distribution

  Use TensorFlow's random_uniform operation to create a TensorFlow Tensor with a random uniform distribution

    2:33
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  PyTorch Tensor To List: How To Convert A PyTorch Tensor To A List

  Use PyTorch's To List (tolist) operation to convert a PyTorch Tensor to a Python list

    2:08
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  Flatten A TensorFlow Tensor

  Use the TensorFlow reshape operation to flatten a TensorFlow Tensor

    3:17
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  Print TensorFlow Tensor Shape

  Use the TensorFlow get_shape operation to print the static shape of a TensorFlow tensor as a list

    2:35
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  Print TensorFlow Version

  Find out which version of TensorFlow is installed in your system by printing the TensorFlow version

    1:16
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  List All Tensor Names In A TensorFlow Graph

  Use the TensorFlow Get Operations Operation to list all Tensor names in a TensorFlow graph

    4:40
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  PyTorch List to Tensor: Convert A Python List To A PyTorch Tensor

  PyTorch List to Tensor - Use the PyTorch Tensor operation (torch.tensor) to convert a Python list object into a PyTorch Tensor

    2:01
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  Use Torchvision CenterCrop Transform To Do A Rectangular Crop Of A PIL Image

  Use Torchvision CenterCrop Transform (torchvision.transforms.CenterCrop) to do a rectangular crop of a PIL image

    3:33
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  Use Torchvision CenterCrop Transform To Do A Square Crop Of A PIL Image

  Use Torchvision CenterCrop Transform (torchvision.transforms.CenterCrop) to do a square crop of a PIL image

    3:40
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  Convert List To TensorFlow Tensor

  Convert a python list into a TensorFlow Tensor using the TensorFlow convert_to_tensor functionality

    2:21
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  Get The Shape Of A PyTorch Tensor As A List Of Integers

  Get the shape of a PyTorch Tensor as a list of integers by using the PyTorch Shape operation and the Python List constructor

    2:28
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  PyTorch Stack: Turn A List Of PyTorch Tensors Into One Tensor

  PyTorch Stack - Use the PyTorch Stack operation (torch.stack) to turn a list of PyTorch Tensors into one tensor

    3:03
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  Check Torchvision Version

  Check the TorchVision version by printing the version parameter

    0:26
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  Create TensorFlow Name Scopes For TensorBoard

  Use TensorFlow Name Scopes (tf.name_scope) to group graph nodes in the TensorBoard web service so that your graph visualization is legible

    6:04
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  Visualize TensorFlow Graph In TensorBoard

  Use TensorFlow Summary File Writer (tf.summary.FileWriter) and the TensorBoard command line unitility to visualize a TensorFlow Graph in the TensorBoard web service

    4:23
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  Launch TensorFlow TensorBoard

  Use the TensorBoard command line utility to launch the TensorFlow TensorBoard web service

    1:23
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  Create TensorFlow Summary File Writer For TensorBoard

  Use TensorFlow Summary File Writer (tf.summary.FileWriter) to create a TensorFlow Summary Event File for TensorBoard

    4:17
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  Add A New Dimension To The End Of A Tensor In PyTorch

  Add a new dimension to the end of a PyTorch tensor by using None-style indexing

    2:10
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  Add A New Dimension To The Middle Of A Tensor In PyTorch

  Add a new dimension to the middle of a PyTorch tensor by using None-style indexing

    2:12
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  Add A New Dimension To The Beginning Of A Tensor In PyTorch

  Add a new dimension to the beginning of a PyTorch tensor by using None-style indexing

    1:37
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  PyTorch numel: Calculate The Number Of Elements In A PyTorch Tensor

  PyTorch numel - Calculate the number of elements in a PyTorch Tensor by using the PyTorch numel operation

    1:22
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  Create A PyTorch Identity Matrix

  Create a PyTorch identity matrix by using the PyTorch eye operation

    1:03
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  Move PyTorch Tensor Data To A Contiguous Chunk Of Memory

  Use the PyTorch contiguous operation to move a PyTorch Tensor's data to a contiguous chunk of memory

    5:59
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  Infer Dimensions While Reshaping A PyTorch Tensor

  Infer dimensions while reshaping a PyTorch tensor by using the PyTorch view operation

    4:00
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  Flatten A PyTorch Tensor

  Flatten A PyTorch Tensor by using the PyTorch view operation

    2:22
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  PyTorch View: Reshape A PyTorch Tensor

  PyTorch View - how to use the PyTorch View (.view(...)) operation to reshape a PyTorch tensor

    3:34
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  Transpose A Matrix In PyTorch

  Transpose A Matrix In PyTorch by using the PyTorch T operation

    1:59
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  Fill A PyTorch Tensor With A Certain Scalar

  Fill A PyTorch Tensor with a certain scalar by using the PyTorch fill operation

    2:09
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  Tell PyTorch To Do An In Place Operation

  Tell PyTorch to do an in-place operation by using an underscore after an operation's name

    2:48
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  Add Two PyTorch Tensors Together

  Add two PyTorch Tensors together by using the PyTorch add operation

    2:00
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  Specify PyTorch Tensor Maximum Value Threshold

  Specify PyTorch Tensor Maximum Value Threshold by using the PyTorch clamp operation

    1:59
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  Specify PyTorch Tensor Minimum Value Threshold

  Specify PyTorch Tensor Minimum Value Threshold by using the PyTorch clamp operation

    2:06
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  PyTorch Clamp: Clip PyTorch Tensor Values To A Range

  Use PyTorch clamp operation to clip PyTorch Tensor values to a specific range

    1:48
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  Generate TensorFlow Tensor Full Of Random Numbers In A Given Range

  Generate TensorFlow Tensor full of random numbers in a given range by using TensorFlow's random_uniform operation

    3:03
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  Use TensorFlow reshape To Infer Reshaped Tensor's New Dimensions

  Use the TensorFlow reshape operation to infer a tensor's new dimensions when reshaping a tensor

    6:28
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  Get The PyTorch Variable Shape

  Get the PyTorch Variable shape by using the PyTorch size operation

    1:56
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  Calculate The Biased Standard Deviation Of All Elements In A PyTorch Tensor

  Calculate the biased standard deviation of all elements in a PyTorch Tensor by using the PyTorch std operation

    4:47
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  Calculate The Unbiased Standard Deviation Of All Elements In A PyTorch Tensor

  Calculate the unbiased standard deviation of all elements in a PyTorch Tensor by using the PyTorch std operation

    5:00
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  Calculate The Power Of Each Element In A PyTorch Tensor For A Given Exponent

  Calculate the power of each element in a PyTorch Tensor for a given exponent by using the PyTorch pow operation

    2:04
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  Calculate The Sum Of All Elements In A PyTorch Tensor

  Calculate the Sum of all elements in a tensor by using the PyTorch sum operation

    2:00
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  Calculate The Mean Value Of All Elements In A PyTorch Tensor

  Calculate the Mean value of all elements in a tensor by using the PyTorch mean operation

    2:01
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  Use TensorFlow reshape To Change The Shape Of A Tensor

  Use TensorFlow reshape to change the shape of a TensorFlow Tensor as long as the number of elements stay the same

    5:29
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  Check For Element Wise Equality Between Two PyTorch Tensors

  Check for element wise equality between two PyTorch tensors using the PyTorch eq equality comparison operation

    3:00
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  tf.matmul: Multiply Two Matricies Using TensorFlow MatMul

  tf.matmul - Multiply two matricies by using TensorFlow's matmul operation

    3:35
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  TensorFlow Element Wise Multiplication

  TensorFlow Element Wise Multiply of Tensors to get the Hadamard product

    4:10
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  tf.stack: How To Use TensorFlow Stack Operation

  tf.stack - How to use tf stack operation to stack a list of TensorFlow tensors

    4:58
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  TensorFlow Equal: Compare Two Tensors Element Wise

  TensorFlow Equal - Compare two tensors element wise for equality

    5:08
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  tf.ones: How To Use tf ones Operation

  tf.ones - How to use tf ones operation to create a TensorFlow ones Tensor

    2:40
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  tf.zeros: How To Use tf zeros Operation

  tf.zeros - How to use tf zeros operation to create a TensorFlow zeros Tensor

    2:52
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  tf.reduce_sum: Sum Along Axis

  tf.reduce_sum - Sum Along Axis Using TensorFlow reduce_sum

    3:33
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  tf.constant_initializer: TensorFlow Constant Initializer

  tf.constant_initializer - Use TensorFlow constant initializer operation to initialize a constant in TensorFlow

    2:58
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  tf.variable: TensorFlow Variable Initialize With NumPy Values

  tf.variable - TensorFlow variable initialize with NumPy Values by using tf's get_variable operation

    3:15
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  tf.constant: Create Tensorflow Constant Tensor

  tf.constant - Create Tensorflow constant tensor with scalar value using tf constant operation.

    3:16
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  TensorFlow Sum: Use tf.add_n To Sum List of Tensors

  TensorFlow Sum - Use TensorFlow's add_n (tf.add_n) to sum list of Tensors

    3:55
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  Initialize TensorFlow Variables With Matrix

  Initialize TensorFlow variables with matrix of your choice. Example with identity matrix.

    3:11
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  TensorFlow Identity Matrix Creation

  TensorFlow Identity Matrix Creation with TensorFlow eye (tf.eye)

    3:03
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  tf.placeholder: Create A TensorFlow Placeholder Tensor

  tf.placeholder - Create A TensorFlow Placeholder Tensor and then when it needs to be evaluated pass a NumPy multi-dimensional array into the feed_dict so that the values are used within the TensorFlow session

    4:39
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  TensorFlow squeeze: Use tf.squeeze to remove a dimension from Tensor

  TensorFlow squeeze - Use tf.squeeze to remove a dimension from Tensor in order to transfer a 1-D Tensor to a Vector

    2:48
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  PyTorch Element Wise Multiplication

  PyTorch Element Wise Multiplication - Calculate the element wise multiplication to get the Hadamard Product

    2:59
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  TensorFlow Add: Add Two TensorFlow Tensors Together

  TensorFlow Add - Use TensorFlow's tf.add to add two Tensors together

    2:57
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  get_tensor_by_name: Get A TensorFlow Variable Tensor By Name

  get_tensor_by_name - TensorFlow get variable by name by using the TensorFlow get_default_graph operation and then the TensorFlow get_tensor_by_name operation

    2:32
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  TensorFlow feed_dict: Use feed_dict To Feed Values To TensorFlow Placeholders

  TensorFlow feed_dict example: Use feed_dict to feed values to TensorFlow placeholders so that you don't run into the error that says you must feed a value for placeholder tensors

    3:35
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  PyTorch Tensor Shape: Get the PyTorch Tensor size

  PyTorch Tensor Shape - Get the PyTorch Tensor size as a PyTorch Size object and as a list of integers

    2:12
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  PyTorch Print Tensor: Print Full Tensor in PyTorch

  PyTorch Print Tensor - Print full tensor in PyTorch so that you can see all of the elements rather than just seeing the truncated or shortened version

    2:27
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  tf.reduce_mean: Calculate Mean of A Tensor Along An Axis Using TensorFlow

  tf.reduce_mean - Use TensorFlow reduce_mean operation to calculate the mean of tensor elements along various dimensions of the tensor

    4:32
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  TensorFlow Initialize Global Variables: Initialize TensorFlow Variables That Depend On Other TensorFlow Variables

  TensorFlow Initialize Global Variables - Initialize TensorFlow Variables That Depend On Other TensorFlow Variables by using the TensorFlow initialized_value functionality

    5:00
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  Convert MXNet NDArray to NumPy Multidimensional Array

  Convert an MXNet NDArray to a NumPy Multidimensional Array so that it retains the specific data type using the asnumpy MXNet function

    2:40
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  PyTorch Variable To NumPy: Convert PyTorch autograd Variable To NumPy Multidimensional Array

  PyTorch Variable To NumPy - Transform a PyTorch autograd Variable to a NumPy Multidimensional Array by extracting the PyTorch Tensor from the Variable and converting the Tensor to the NumPy array

    3:30
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  tf.reduce_max: Calculate Max Of A Tensor Along An Axis Using TensorFlow

  tf.reduce_max - Calculate the max of a TensorFlow tensor along a certain axis of the tensor using the TensorFlow reduce_max operation

    6:24
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  TensorFlow Max: Use tf.reduce_max To Get Max Value Of A TensorFlow Tensor

  TensorFlow Max - Use tf.reduce_max to get max value of a TensorFlow Tensor

    2:34
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  tf.reshape: Use TensorFlow reshape To Convert A Tensor To A Vector

  tf.reshape - Use TensorFlow reshape to convert a tensor to a vector by understanding the two arguments you must pass to the reshape operation and how the special value of negative one flattens the input tensor

    4:18
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  MXNet NDArray: Convert NumPy Array To MXNet NDArray

  MXNet NDArray - Convert A NumPy multidimensional array to an MXNet NDArray so that it retains the specific data type

    3:47
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  PyTorch Tensor to NumPy: Convert A PyTorch Tensor To A Numpy Multidimensional Array

  PyTorch Tensor to NumPy - Convert a PyTorch tensor to a NumPy multidimensional array so that it retains the specific data type

    3:57
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  TensorFlow Print: Print The Value Of A Tensor Object In TensorFlow

  TensorFlow Print - Print the value of a tensor object in TensorFlow by understanding the difference between building the computational graph and running the computational graph

    3:36
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  tf.concat: Concatenate TensorFlow Tensors Along A Given Dimension

  tf.concat - Use tf.concat, TensorFlow's concatenation operation, to concatenate TensorFlow tensors along a given dimension

    4:55
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  tf.random_uniform: Generate A Random Tensor In Tensorflow

  tf.random_uniform - Generate a random tensor in TensorFlow so that you can use it and maintain it for further use even if you call session run multiple times

    4:09
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  PyTorch Variable: Create A PyTorch Variable

  PyTorch Variable - create a PyTorch Variable which wraps a PyTorch Tensor and records operations applied to it

    1:36
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  PyTorch NumPy to tensor: Convert A NumPy Array To A PyTorch Tensor

  PyTorch NumPy to tensor - Convert a NumPy Array into a PyTorch Tensor so that it retains the specific data type

    1:53
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  PyTorch Concatenate: Concatenate PyTorch Tensors Along A Given Dimension With PyTorch cat

  PyTorch Concatenate - Use PyTorch cat to concatenate a list of PyTorch tensors along a given dimension

    4:45
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  PyTorch Change Tensor Type: Cast A PyTorch Tensor To Another Type

  PyTorch change Tensor type - convert and change a PyTorch tensor to another type

    3:06
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  PyTorch Tensor Type: Print And Check PyTorch Tensor Type

  PyTorch Tensor Type - print out the PyTorch tensor type without printing out the whole PyTorch tensor

    1:42
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  torch create tensor: Construct a PyTorch Tensor

  torch create tensor - Create an uninitialized PyTorch Tensor and an initialized PyTorch Tensor

    1:49