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Advanced Interview Questions on TensorFlow

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In this article, we have presented advanced interview questions on TensorFlow with multiple options to choose from. Select an answer to find out if you got it right and get explanation for the answer.

This will help you get prepared for tough Interviews on TensorFlow, Google's Machine Learning framework.

Which datatype is not supported in TensorFlow as of v2.5.0?

FP8
FP32
INT8
INT32
FP8 (Floating point, 8 bits) is not supported in TensorFlow as of v2.5.0. Over 30 datatypes are supported in TensorFlow including INT8, INT32, UINT8 and many others. It has been proposed to include FP8 in later versions.

Can we add a new operation in TensorFlow without modifying the source code?

Yes
No
Depends on operations
Depends on datatype
A new operation can be added in TensorFlow without modifying the source code. The implementation of the new op should be in C++ and it should be registered. The instructions to do this is at: tensorflow.org/guide/create_op

Intel's OneDNN is officially supported in TensorFlow as an optimized version. Which environment variable is used to enable logs in this version?

MKLDNN_VERBOSE
ONEDNN_VERBOSE
ONEDNN_LOGS
MKLDNN_LOGS
Setting the environment variable MKLDNN_VERBOSE to 1

Consider the following error:

AttributeError: module 'tensorflow' has no attribute 'GraphDef'

If we get the above error, what might be the issue?

Using wrong TF version
Using wrong API
Corrupted TF build
Error in graph optimization
It mentions that tensorflow module does not have the attribute GraphDef. This is because GraphDef was removed in later versions of TensorFlow that is following v2.x. You need to have experience porting code from TFv1.x to TFv2.x to understand this.

What is the additional attribute that is stored by SavedModel compared to Checkpoints in TensorFlow?

Serialized description of computation
Number of operations
Value of different variables
Description of links between ops
SavedModel has serialized description of the computation in addition to a Checkpoint. Checkpoint only has the saved value of different variables. When it comes to save a pre-trained graph, then we have two options in TensorFlow: Checkpoint and SavedModel.

What of the following is not a valid file extension of a Checkpoint file in TensorFlow?

ckpt.value
ckpt.data
ckpt.meta
ckpt.index
The file extension of a Checkout file is .ckpt. It can have different files which can have extensions like ckpt.meta, ckpt.data and ckpt.index. There is no extension like ckpt.value.

What does "Pin to host optimizer" in TensorFlow graph optimizations do?

Swaps small operations onto CPU
Scoped allocators to reduce data movement
Automatically parallelizes graphs
Optimizes function library
"Pin to host optimizer" is a TensorFlow graph optimizations. It swaps small operations onto the CPU and is turned off by default.

In the function tf.nn.conv2d of TensorFlow, what is the dimension of the parameter "filters"?

4
2
1
Any value
Filters in the operation tf.nn.conv2d is a 4 dimensional tensor. The dimensions are: filter_height, filter_width, in_channels and out_channels.

In the operation tf.nn.avg_pool3d, what is the data type of the input is supported?

NDHWC
NHWC
NCHW
NCHWc8
In TensorFlow, the operation tf.nn.avg_pool3d supports only two data formats namely: NDHWC and NCDHW.

Which operation in TensorFlow is used for bitwise AND operation between two tensors?

tf.bitwise.bitwise_and
tf.bitwise.and
tf.add
tf.bitwise_and
tf.bitwise.bitwise_and() is the operation in TensorFlow which is used for bitwise AND operation between two tensors of any datatype (DType) supported by TensorFlow.

There are two operations in TensorFlow for 2D Convolution namely tf.nn.conv2d and tf.raw_ops.Conv2D. Which attribute is additional in tf.raw_ops.Conv2D?

use_cudnn_on_gpu
dilations
padding
data_format
tf.raw_ops.Conv2D has two additional attributes namely use_cudnn_on_gpu and explicit_paddings. Operations in tf.raw_ops provide access to low level functions in TensorFlow.

With these questions at OpenGenus, you must have had a strong test of your advanced TensorFlow skills. Enjoy.

Advanced Interview Questions on TensorFlow
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