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lunderberg pushed a commit to branch main
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new 1698793226 [CI] Disable testing that downloads from mxnet (#16546)
1698793226 is described below
commit 1698793226ef326af2a8559918b6dac20a2e0932
Author: Eric Lunderberg <[email protected]>
AuthorDate: Fri Feb 9 14:42:25 2024 -0600
[CI] Disable testing that downloads from mxnet (#16546)
* [Testing] Disable testing that downloads from mxnet
The mxnet project was archived in
2023-09 ([link](https://attic.apache.org/projects/mxnet.html)).
Downloads from the mxnet AWS
links (e.g.
`https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip`)
no longer can be performed. This commit disables TVM CI steps that
depend on downloading models from these locations.
* Disable build.rs in resnet Rust example
---
gallery/how_to/compile_models/from_mxnet.py | 8 +++++++-
gallery/how_to/deploy_models/deploy_model_on_nano.py | 8 +++++++-
gallery/how_to/deploy_models/deploy_model_on_rasp.py | 8 +++++++-
gallery/how_to/deploy_models/deploy_quantized.py | 12 +++++++++---
.../how_to/extend_tvm/bring_your_own_datatypes.py | 8 +++++++-
.../tune_with_autoscheduler/tune_network_arm.py | 11 ++++++++---
.../tune_with_autoscheduler/tune_network_cuda.py | 8 ++++++--
.../tune_with_autoscheduler/tune_network_mali.py | 10 ++++++++--
.../tune_with_autoscheduler/tune_network_x86.py | 20 +++++++++++++-------
rust/tvm/examples/resnet/build.rs | 6 ++++++
rust/tvm/examples/resnet/src/main.rs | 5 +++++
tests/python/frontend/mxnet/test_forward.py | 5 ++++-
.../quantization/test_quantization_accuracy.py | 19 +++++++++++++------
vta/scripts/tune_resnet.py | 8 ++++++--
vta/tutorials/autotvm/tune_alu_vta.py | 7 ++++++-
vta/tutorials/autotvm/tune_relay_vta.py | 8 +++++++-
vta/tutorials/frontend/deploy_classification.py | 7 ++++++-
17 files changed, 125 insertions(+), 33 deletions(-)
diff --git a/gallery/how_to/compile_models/from_mxnet.py
b/gallery/how_to/compile_models/from_mxnet.py
index 0694d2aed0..132f098d92 100644
--- a/gallery/how_to/compile_models/from_mxnet.py
+++ b/gallery/how_to/compile_models/from_mxnet.py
@@ -37,6 +37,7 @@ https://mxnet.apache.org/versions/master/install/index.html
# sphinx_gallery_start_ignore
# sphinx_gallery_requires_cuda = True
# sphinx_gallery_end_ignore
+import sys
import mxnet as mx
import tvm
import tvm.relay as relay
@@ -51,7 +52,12 @@ from mxnet.gluon.model_zoo.vision import get_model
from PIL import Image
from matplotlib import pyplot as plt
-block = get_model("resnet18_v1", pretrained=True)
+try:
+ block = get_model("resnet18_v1", pretrained=True)
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
+
img_url = "https://github.com/dmlc/mxnet.js/blob/main/data/cat.png?raw=true";
img_name = "cat.png"
synset_url = "".join(
diff --git a/gallery/how_to/deploy_models/deploy_model_on_nano.py
b/gallery/how_to/deploy_models/deploy_model_on_nano.py
index abd0b3fab6..761187e2d7 100644
--- a/gallery/how_to/deploy_models/deploy_model_on_nano.py
+++ b/gallery/how_to/deploy_models/deploy_model_on_nano.py
@@ -106,12 +106,18 @@ from tvm.contrib.download import download_testdata
# `MXNet Gluon model zoo
<https://mxnet.apache.org/api/python/gluon/model_zoo.html>`_.
# You can found more details about this part at tutorial
:ref:`tutorial-from-mxnet`.
+import sys
+
from mxnet.gluon.model_zoo.vision import get_model
from PIL import Image
import numpy as np
# one line to get the model
-block = get_model("resnet18_v1", pretrained=True)
+try:
+ block = get_model("resnet18_v1", pretrained=True)
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
######################################################################
# In order to test our model, here we download an image of cat and
diff --git a/gallery/how_to/deploy_models/deploy_model_on_rasp.py
b/gallery/how_to/deploy_models/deploy_model_on_rasp.py
index de4ed9aff0..5196ae9ce1 100644
--- a/gallery/how_to/deploy_models/deploy_model_on_rasp.py
+++ b/gallery/how_to/deploy_models/deploy_model_on_rasp.py
@@ -99,12 +99,18 @@ from tvm.contrib.download import download_testdata
# `MXNet Gluon model zoo
<https://mxnet.apache.org/api/python/gluon/model_zoo.html>`_.
# You can found more details about this part at tutorial
:ref:`tutorial-from-mxnet`.
+import sys
+
from mxnet.gluon.model_zoo.vision import get_model
from PIL import Image
import numpy as np
# one line to get the model
-block = get_model("resnet18_v1", pretrained=True)
+try:
+ block = get_model("resnet18_v1", pretrained=True)
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
######################################################################
# In order to test our model, here we download an image of cat and
diff --git a/gallery/how_to/deploy_models/deploy_quantized.py
b/gallery/how_to/deploy_models/deploy_quantized.py
index f1b45dd7c1..2cdb7da5f8 100644
--- a/gallery/how_to/deploy_models/deploy_quantized.py
+++ b/gallery/how_to/deploy_models/deploy_quantized.py
@@ -27,6 +27,9 @@ In this tutorial, we will import a GluonCV pre-trained model
on ImageNet to
Relay, quantize the Relay model and then perform the inference.
"""
+import logging
+import os
+import sys
import tvm
from tvm import te
@@ -34,8 +37,7 @@ from tvm import relay
import mxnet as mx
from tvm.contrib.download import download_testdata
from mxnet import gluon
-import logging
-import os
+
batch_size = 1
model_name = "resnet18_v1"
@@ -157,7 +159,11 @@ def run_inference(mod):
def main():
- mod, params = get_model()
+ try:
+ mod, params = get_model()
+ except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ return
mod = quantize(mod, params, data_aware=True)
run_inference(mod)
diff --git a/gallery/how_to/extend_tvm/bring_your_own_datatypes.py
b/gallery/how_to/extend_tvm/bring_your_own_datatypes.py
index f5ff89717c..e502aff3e0 100644
--- a/gallery/how_to/extend_tvm/bring_your_own_datatypes.py
+++ b/gallery/how_to/extend_tvm/bring_your_own_datatypes.py
@@ -58,6 +58,8 @@ If you would like to try this with your own datatype library,
first bring the li
# --------------------
#
# We'll begin by writing a simple program in TVM; afterwards, we will re-write
it to use custom datatypes.
+import sys
+
import tvm
from tvm import relay
@@ -253,7 +255,11 @@ def get_cat_image():
return np.asarray(img, dtype="float32")
-module, params = get_mobilenet()
+try:
+ module, params = get_mobilenet()
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
######################################################################
# It's easy to execute MobileNet with native TVM:
diff --git a/gallery/how_to/tune_with_autoscheduler/tune_network_arm.py
b/gallery/how_to/tune_with_autoscheduler/tune_network_arm.py
index adc9c9fbb2..0b59038f19 100644
--- a/gallery/how_to/tune_with_autoscheduler/tune_network_arm.py
+++ b/gallery/how_to/tune_with_autoscheduler/tune_network_arm.py
@@ -49,6 +49,7 @@ __name__ == "__main__":` block.
import numpy as np
import os
+import sys
import tvm
from tvm import relay, auto_scheduler
@@ -264,9 +265,13 @@ log_file = "%s-%s-B%d-%s.json" % (network, layout,
batch_size, target.kind.name)
# Extract tasks from the network
print("Get model...")
-mod, params, input_shape, output_shape = get_network(
- network, batch_size, layout, dtype=dtype, use_sparse=use_sparse
-)
+try:
+ mod, params, input_shape, output_shape = get_network(
+ network, batch_size, layout, dtype=dtype, use_sparse=use_sparse
+ )
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
print("Extract tasks...")
tasks, task_weights = auto_scheduler.extract_tasks(mod["main"], params, target)
diff --git a/gallery/how_to/tune_with_autoscheduler/tune_network_cuda.py
b/gallery/how_to/tune_with_autoscheduler/tune_network_cuda.py
index 6709964103..41e7e8fb41 100644
--- a/gallery/how_to/tune_with_autoscheduler/tune_network_cuda.py
+++ b/gallery/how_to/tune_with_autoscheduler/tune_network_cuda.py
@@ -44,7 +44,7 @@ get it to run, you will need to wrap the body of this
tutorial in a :code:`if
__name__ == "__main__":` block.
"""
-
+import sys
import numpy as np
import tvm
@@ -152,7 +152,11 @@ log_file = "%s-%s-B%d-%s.json" % (network, layout,
batch_size, target.kind.name)
# Extract tasks from the network
print("Extract tasks...")
-mod, params, input_shape, output_shape = get_network(network, batch_size,
layout, dtype=dtype)
+try:
+ mod, params, input_shape, output_shape = get_network(network, batch_size,
layout, dtype=dtype)
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
tasks, task_weights = auto_scheduler.extract_tasks(mod["main"], params, target)
for idx, task in enumerate(tasks):
diff --git a/gallery/how_to/tune_with_autoscheduler/tune_network_mali.py
b/gallery/how_to/tune_with_autoscheduler/tune_network_mali.py
index ab754ea30f..1c531a5303 100644
--- a/gallery/how_to/tune_with_autoscheduler/tune_network_mali.py
+++ b/gallery/how_to/tune_with_autoscheduler/tune_network_mali.py
@@ -44,6 +44,8 @@ get it to run, you will need to wrap the body of this
tutorial in a :code:`if
__name__ == "__main__":` block.
"""
+import os
+import sys
import numpy as np
@@ -51,7 +53,7 @@ import tvm
from tvm import relay, auto_scheduler
import tvm.relay.testing
from tvm.contrib import graph_executor
-import os
+
#################################################################
# Define a Network
@@ -169,7 +171,11 @@ device_key = "rk3399"
# Extract tasks from the network
print("Extract tasks...")
-mod, params, input_shape, output_shape = get_network(network, batch_size,
layout, dtype=dtype)
+try:
+ mod, params, input_shape, output_shape = get_network(network, batch_size,
layout, dtype=dtype)
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
tasks, task_weights = auto_scheduler.extract_tasks(mod["main"], params, target)
for idx, task in enumerate(tasks):
diff --git a/gallery/how_to/tune_with_autoscheduler/tune_network_x86.py
b/gallery/how_to/tune_with_autoscheduler/tune_network_x86.py
index 6eb1b79bfe..96df3942ab 100644
--- a/gallery/how_to/tune_with_autoscheduler/tune_network_x86.py
+++ b/gallery/how_to/tune_with_autoscheduler/tune_network_x86.py
@@ -45,6 +45,7 @@ get it to run, you will need to wrap the body of this
tutorial in a :code:`if
__name__ == "__main__":` block.
"""
+import sys
import numpy as np
@@ -168,13 +169,18 @@ log_file = "%s-%s-B%d-%s.json" % (network, layout,
batch_size, target.kind.name)
# Extract tasks from the network
print("Get model...")
-mod, params, input_shape, output_shape = get_network(
- network,
- batch_size,
- layout,
- dtype=dtype,
- use_sparse=use_sparse,
-)
+try:
+ mod, params, input_shape, output_shape = get_network(
+ network,
+ batch_size,
+ layout,
+ dtype=dtype,
+ use_sparse=use_sparse,
+ )
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
+
print("Extract tasks...")
tasks, task_weights = auto_scheduler.extract_tasks(mod["main"], params, target)
diff --git a/rust/tvm/examples/resnet/build.rs
b/rust/tvm/examples/resnet/build.rs
index 9e3a76433f..45e4d6d658 100644
--- a/rust/tvm/examples/resnet/build.rs
+++ b/rust/tvm/examples/resnet/build.rs
@@ -21,6 +21,10 @@ use anyhow::{Context, Result};
use std::{io::Write, path::Path, process::Command};
fn main() -> Result<()> {
+ // Currently disabled, as it depends on the no-longer-supported
+ // mxnet repo to download resnet.
+
+ /*
let out_dir = std::env::var("CARGO_MANIFEST_DIR")?;
let python_script = concat!(env!("CARGO_MANIFEST_DIR"),
"/src/build_resnet.py");
let synset_txt = concat!(env!("CARGO_MANIFEST_DIR"), "/synset.txt");
@@ -53,5 +57,7 @@ fn main() -> Result<()> {
);
println!("cargo:rustc-link-search=native={}", out_dir);
+ */
+
Ok(())
}
diff --git a/rust/tvm/examples/resnet/src/main.rs
b/rust/tvm/examples/resnet/src/main.rs
index c22d55f2e4..0ea8c4cf8b 100644
--- a/rust/tvm/examples/resnet/src/main.rs
+++ b/rust/tvm/examples/resnet/src/main.rs
@@ -31,6 +31,10 @@ use tvm_rt::graph_rt::GraphRt;
use tvm_rt::*;
fn main() -> anyhow::Result<()> {
+ // Currently disabled, as it depends on the no-longer-supported
+ // mxnet repo to download resnet.
+
+ /*
let dev = Device::cpu(0);
println!("{}", concat!(env!("CARGO_MANIFEST_DIR"), "/cat.png"));
@@ -134,6 +138,7 @@ fn main() -> anyhow::Result<()> {
"input image belongs to the class `{}` with probability {}",
label, max_prob
);
+ */
Ok(())
}
diff --git a/tests/python/frontend/mxnet/test_forward.py
b/tests/python/frontend/mxnet/test_forward.py
index 880416c7be..cf206a3d52 100644
--- a/tests/python/frontend/mxnet/test_forward.py
+++ b/tests/python/frontend/mxnet/test_forward.py
@@ -42,7 +42,10 @@ def verify_mxnet_frontend_impl(
if gluon_impl:
def get_gluon_output(name, x):
- net = vision.get_model(name)
+ try:
+ net = vision.get_model(name)
+ except RuntimeError:
+ pytest.skip(reason="mxnet downloads no longer supported")
net.collect_params().initialize(mx.init.Xavier())
net_sym = gluon.nn.SymbolBlock(
outputs=net(mx.sym.var("data")),
diff --git a/tests/python/nightly/quantization/test_quantization_accuracy.py
b/tests/python/nightly/quantization/test_quantization_accuracy.py
index 66153831d8..7eebdd17f2 100644
--- a/tests/python/nightly/quantization/test_quantization_accuracy.py
+++ b/tests/python/nightly/quantization/test_quantization_accuracy.py
@@ -14,15 +14,19 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
+
from collections import namedtuple
-import tvm
-from tvm import relay
-from tvm.relay import quantize as qtz
-import mxnet as mx
-from mxnet import gluon
import logging
import os
+
+import mxnet as mx
+from mxnet import gluon
+import pytest
+
+import tvm
import tvm.testing
+from tvm import relay
+from tvm.relay import quantize as qtz
logging.basicConfig(level=logging.INFO)
@@ -69,7 +73,10 @@ def get_val_data(model_name, rec_val, batch_size,
num_workers=4):
def get_model(model_name, batch_size, qconfig, original=False):
- gluon_model = gluon.model_zoo.vision.get_model(model_name, pretrained=True)
+ try:
+ gluon_model = gluon.model_zoo.vision.get_model(model_name,
pretrained=True)
+ except RuntimeError:
+ pytest.skip(reason="mxnet downloads no longer supported")
img_size = 299 if model_name == "inceptionv3" else 224
data_shape = (batch_size, 3, img_size, img_size)
mod, params = relay.frontend.from_mxnet(gluon_model, {"data": data_shape})
diff --git a/vta/scripts/tune_resnet.py b/vta/scripts/tune_resnet.py
index 2c284f05a0..7fa6ec42ce 100644
--- a/vta/scripts/tune_resnet.py
+++ b/vta/scripts/tune_resnet.py
@@ -17,7 +17,7 @@
"""Perform ResNet autoTVM tuning on VTA using Relay."""
-import argparse, os, time
+import argparse, os, sys, time
from mxnet.gluon.model_zoo import vision
import numpy as np
from PIL import Image
@@ -285,7 +285,11 @@ if __name__ == "__main__":
# Compile Relay program
print("Initial compile...")
- relay_prog, params = compile_network(opt, env, target)
+ try:
+ relay_prog, params = compile_network(opt, env, target)
+ except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
# Register VTA tuning tasks
register_vta_tuning_tasks()
diff --git a/vta/tutorials/autotvm/tune_alu_vta.py
b/vta/tutorials/autotvm/tune_alu_vta.py
index 8a4db13ac4..8ee58fe990 100644
--- a/vta/tutorials/autotvm/tune_alu_vta.py
+++ b/vta/tutorials/autotvm/tune_alu_vta.py
@@ -20,6 +20,7 @@ Auto-tuning a ALU fused op on VTA
"""
import os
+import sys
from mxnet.gluon.model_zoo import vision
import numpy as np
from PIL import Image
@@ -337,4 +338,8 @@ def tune_and_evaluate(tuning_opt):
# Run the tuning and evaluate the results
-tune_and_evaluate(tuning_option)
+try:
+ tune_and_evaluate(tuning_option)
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
diff --git a/vta/tutorials/autotvm/tune_relay_vta.py
b/vta/tutorials/autotvm/tune_relay_vta.py
index dc5bd46227..b5de247883 100644
--- a/vta/tutorials/autotvm/tune_relay_vta.py
+++ b/vta/tutorials/autotvm/tune_relay_vta.py
@@ -54,6 +54,8 @@ log file to get the best knob parameters.
# Now return to python code. Import packages.
import os
+import sys
+
from mxnet.gluon.model_zoo import vision
import numpy as np
from PIL import Image
@@ -471,7 +473,11 @@ def tune_and_evaluate(tuning_opt):
# Run the tuning and evaluate the results
-tune_and_evaluate(tuning_option)
+try:
+ tune_and_evaluate(tuning_option)
+except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
######################################################################
# Sample Output
diff --git a/vta/tutorials/frontend/deploy_classification.py
b/vta/tutorials/frontend/deploy_classification.py
index f1e4926a32..c741a1678f 100644
--- a/vta/tutorials/frontend/deploy_classification.py
+++ b/vta/tutorials/frontend/deploy_classification.py
@@ -43,6 +43,7 @@ from __future__ import absolute_import, print_function
import argparse, json, os, requests, sys, time
from io import BytesIO
from os.path import join, isfile
+import sys
from PIL import Image
from mxnet.gluon.model_zoo import vision
@@ -163,7 +164,11 @@ with autotvm.tophub.context(target):
shape_dict = {"data": (env.BATCH, 3, 224, 224)}
# Get off the shelf gluon model, and convert to relay
- gluon_model = vision.get_model(model, pretrained=True)
+ try:
+ gluon_model = vision.get_model(model, pretrained=True)
+ except RuntimeError:
+ print("Downloads from mxnet no longer supported", file=sys.stderr)
+ sys.exit(0)
# Measure build start time
build_start = time.time()
![https://github.com/dmlc/mxnet.js/blob/main/data/cat.png?raw=true"](https://github.com/dmlc/mxnet.js/blob/main/data/cat.png?raw=true"){kind=link}