[ci] Redirect sphinx-gallery URLs to S3

gallery/how_to/compile_models/from_coreml.py

@@ -34,6 +34,12 @@
 or please refer to official site
 https://github.com/apple/coremltools
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import tvm
 from tvm import te
 import tvm.relay as relay

gallery/how_to/compile_models/from_darknet.py

@@ -31,6 +31,12 @@
   pip install opencv-python
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 # numpy and matplotlib
 import numpy as np
 import matplotlib.pyplot as plt

gallery/how_to/compile_models/from_keras.py

@@ -34,6 +34,12 @@
 or please refer to official site
 https://keras.io/#installation
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import tvm
 from tvm import te
 import tvm.relay as relay

gallery/how_to/compile_models/from_mxnet.py

@@ -35,6 +35,12 @@
 or please refer to official installation guide.
 https://mxnet.apache.org/versions/master/install/index.html
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 # some standard imports
 import mxnet as mx
 import tvm

gallery/how_to/compile_models/from_oneflow.py

@@ -35,6 +35,12 @@
 
 Currently, TVM supports OneFlow 0.7.0. Other versions may be unstable.
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import os, math
 from matplotlib import pyplot as plt
 import numpy as np

gallery/how_to/compile_models/from_onnx.py

@@ -32,6 +32,12 @@
 or please refer to official site.
 https://github.com/onnx/onnx
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import onnx
 import numpy as np
 import tvm

gallery/how_to/compile_models/from_paddle.py

@@ -30,6 +30,12 @@
 or please refer to official site.
 https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import tarfile
 import paddle
 import numpy as np

gallery/how_to/compile_models/from_pytorch.py

@@ -41,6 +41,12 @@
 be unstable.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import tvm
 from tvm import relay
 

gallery/how_to/compile_models/from_tensorflow.py

@@ -24,6 +24,12 @@
 Please refer to https://www.tensorflow.org/install
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 # tvm, relay
 import tvm
 from tvm import te

gallery/how_to/compile_models/from_tflite.py

@@ -52,6 +52,12 @@
 
 Below you can find an example on how to compile TFLite model using TVM.
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 ######################################################################
 # Utils for downloading and extracting zip files
 # ----------------------------------------------

gallery/how_to/deploy_models/deploy_model_on_android.py

@@ -25,6 +25,12 @@
 This is an example of using Relay to compile a keras model and deploy it on Android device.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import os
 import numpy as np
 from PIL import Image

gallery/how_to/deploy_models/deploy_model_on_rasp.py

@@ -26,6 +26,12 @@
 it on Raspberry Pi.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import tvm
 from tvm import te
 import tvm.relay as relay

gallery/how_to/deploy_models/deploy_object_detection_pytorch.py

@@ -40,6 +40,12 @@
 be unstable.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import tvm
 from tvm import relay
 from tvm import relay

gallery/how_to/deploy_models/deploy_prequantized.py

@@ -28,6 +28,12 @@
 Once loaded, we can run compiled, quantized models on any hardware TVM supports.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 #################################################################################
 # First, necessary imports
 from PIL import Image

gallery/how_to/deploy_models/deploy_prequantized_tflite.py

@@ -42,6 +42,12 @@
 
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 ###############################################################################
 # Necessary imports
 # -----------------

gallery/how_to/deploy_models/deploy_quantized.py

@@ -27,6 +27,12 @@
 Relay, quantize the Relay model and then perform the inference.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import tvm
 from tvm import te
 from tvm import relay

gallery/how_to/deploy_models/deploy_sparse.py

@@ -70,6 +70,12 @@
 sparse speed using fake weights to see the benefit of structured sparsity.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 ###############################################################################
 # Load Required Modules
 # ---------------------

gallery/how_to/deploy_models/deploy_ssd_gluoncv.py

@@ -23,6 +23,12 @@
 This article is an introductory tutorial to deploy SSD models with TVM.
 We will use GluonCV pre-trained SSD model and convert it to Relay IR
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import tvm
 from tvm import te
 

gallery/how_to/extend_tvm/bring_your_own_datatypes.py

@@ -52,6 +52,12 @@
     ctypes.CDLL('my-datatype-lib.so', ctypes.RTLD_GLOBAL)
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 ######################
 # A Simple TVM Program
 # --------------------

gallery/how_to/extend_tvm/low_level_custom_pass.py

@@ -40,6 +40,12 @@
   take a look at ``python/tvm/build_module.py`` to get some basics.
 
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import tvm
 from tvm import te
 import numpy as np

gallery/how_to/extend_tvm/use_pass_infra.py

@@ -40,6 +40,12 @@
 The same approach can be used for tir as well.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import numpy as np
 import tvm
 from tvm import te

gallery/how_to/extend_tvm/use_pass_instrument.py

@@ -33,6 +33,12 @@
 This tutorial demonstrates how developers can use ``PassContext`` to instrument
 passes. Please also refer to the :ref:`pass-infra`.
 """
+
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
 import tvm
 import tvm.relay as relay
 from tvm.relay.testing import resnet

gallery/how_to/optimize_operators/opt_conv_cuda.py

@@ -30,6 +30,12 @@
 
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 ################################################################
 # Preparation and Algorithm
 # -------------------------

gallery/how_to/optimize_operators/opt_conv_tensorcore.py

@@ -27,6 +27,12 @@
 
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 ################################################################
 # TensorCore Introduction
 # -----------------------

gallery/how_to/optimize_operators/opt_gemm.py

@@ -48,6 +48,12 @@
 Intel i7-4770HQ CPU. The cache line size should be 64 bytes for all the x86 CPUs.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 ################################################################################################
 # Preparation and Baseline
 # ------------------------

gallery/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.py

@@ -37,6 +37,12 @@
 __name__ == "__main__":` block.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import os
 
 import numpy as np

gallery/how_to/tune_with_autoscheduler/tune_network_arm.py

@@ -46,6 +46,12 @@
 __name__ == "__main__":` block.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import numpy as np
 import os
 

gallery/how_to/tune_with_autoscheduler/tune_network_cuda.py

@@ -44,6 +44,12 @@
 __name__ == "__main__":` block.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import numpy as np
 
 import tvm

gallery/how_to/tune_with_autoscheduler/tune_network_mali.py

@@ -44,6 +44,12 @@
 __name__ == "__main__":` block.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import numpy as np
 
 import tvm

gallery/how_to/tune_with_autoscheduler/tune_network_x86.py

@@ -45,6 +45,12 @@
 __name__ == "__main__":` block.
 """
 
+# sphinx_gallery_start_ignore
+import tvm
+
+tvm.testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
 import numpy as np
 
 import tvm