[docs] Remove empty code blocks

This fixes some of the issues highlighted in #13668, the parser that
checks to ensure that the hidden import is placed in the right spot was
incorrect, this includes some fixes to get it working for the cases in
that issue.

Author: driazati

gallery/how_to/compile_models/from_darknet.py

@@ -31,13 +31,12 @@
   pip install opencv-python
 """
 
+# numpy and matplotlib
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
-
-# numpy and matplotlib
 import numpy as np
 import matplotlib.pyplot as plt
 import sys

gallery/how_to/compile_models/from_tensorflow.py

@@ -24,13 +24,12 @@
 Please refer to https://www.tensorflow.org/install
 """
 
+# tvm, relay
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
-
-# tvm, relay
 import tvm
 from tvm import te
 from tvm import relay

gallery/how_to/deploy_models/deploy_prequantized.py

@@ -28,14 +28,15 @@
 Once loaded, we can run compiled, quantized models on any hardware TVM supports.
 """
 
+#################################################################################
+# First, necessary imports
+
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
 
-#################################################################################
-# First, necessary imports
 from PIL import Image
 
 import numpy as np

gallery/how_to/deploy_models/deploy_prequantized_tflite.py

@@ -42,15 +42,16 @@
 
 """
 
+###############################################################################
+# Necessary imports
+# -----------------
+
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
 
-###############################################################################
-# Necessary imports
-# -----------------
 import os
 
 import numpy as np

gallery/how_to/deploy_models/deploy_sparse.py

@@ -70,17 +70,18 @@
 sparse speed using fake weights to see the benefit of structured sparsity.
 """
 
+###############################################################################
+# Load Required Modules
+# ---------------------
+# Other than TVM, scipy, the latest transformers, and
+# tensorflow 2.2+ are required.
+
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
 
-###############################################################################
-# Load Required Modules
-# ---------------------
-# Other than TVM, scipy, the latest transformers, and
-# tensorflow 2.2+ are required.
 import os
 import tvm
 import time

gallery/how_to/extend_tvm/bring_your_own_datatypes.py

@@ -52,17 +52,18 @@
     ctypes.CDLL('my-datatype-lib.so', ctypes.RTLD_GLOBAL)
 """
 
+######################
+# A Simple TVM Program
+# --------------------
+#
+# We'll begin by writing a simple program in TVM; afterwards, we will re-write it to use custom datatypes.
+
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
 
-######################
-# A Simple TVM Program
-# --------------------
-#
-# We'll begin by writing a simple program in TVM; afterwards, we will re-write it to use custom datatypes.
 import tvm
 from tvm import relay
 

gallery/how_to/optimize_operators/opt_conv_cuda.py

@@ -30,12 +30,6 @@
 
 """
 
-# sphinx_gallery_start_ignore
-from tvm import testing
-
-testing.utils.install_request_hook(depth=3)
-# sphinx_gallery_end_ignore
-
 ################################################################
 # Preparation and Algorithm
 # -------------------------
@@ -44,7 +38,12 @@
 # dimensions. The batch size is 256. Convolution filters contain 512 filters
 # of size 3 x 3.  We use stride size 1 and padding size 1 for the
 # convolution. The following code defines the convolution algorithm in TVM.
-#
+
+# sphinx_gallery_start_ignore
+from tvm import testing
+
+testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 
 import numpy as np
 import tvm

gallery/how_to/optimize_operators/opt_gemm.py

@@ -48,19 +48,19 @@
 Intel i7-4770HQ CPU. The cache line size should be 64 bytes for all the x86 CPUs.
 """
 
-# sphinx_gallery_start_ignore
-from tvm import testing
-
-testing.utils.install_request_hook(depth=3)
-# sphinx_gallery_end_ignore
-
 ################################################################################################
 # Preparation and Baseline
 # ------------------------
 # In this tutorial, we will demo how to use TVM to optimize matrix multiplication.
 # Before actually demonstrating, we first define these variables.
 # Then we write a baseline implementation, the simplest way to write a matrix multiplication in TVM.
 
+# sphinx_gallery_start_ignore
+from tvm import testing
+
+testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import tvm
 import tvm.testing
 from tvm import te

gallery/how_to/work_with_pytorch/using_as_torch.py

@@ -24,13 +24,12 @@
 Using the decorator `as_torch`, users can wrap TVMScript code into a PyTorch nn.Module naturally.
 """
 
+# Import PyTorch, as well as necessary libraries
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
-
-# Import PyTorch, as well as necessary libraries
 import torch
 import torch.nn.functional as F
 import torch.utils.benchmark as benchmark

gallery/how_to/work_with_pytorch/using_optimized_torch.py

@@ -24,13 +24,12 @@
 To follow this tutorial, PyTorch, as well as TorchVision, should be installed.
 """
 
+# Import PyTorch
 # sphinx_gallery_start_ignore
 from tvm import testing
 
 testing.utils.install_request_hook(depth=3)
 # sphinx_gallery_end_ignore
-
-# Import PyTorch
 import torch
 import torch.nn as nn
 import torch.nn.functional as F