Create library for converting pytorch to caffe2 and examples #69

houseroad · 2017-11-17T00:01:41Z

Base on this example, we can create notebooks which explain how to compare the results and performance.

bddppq · 2017-11-17T00:17:49Z

onnx_caffe2/pytorch_caffe2.py

+log = logging.getLogger(__name__)
+
+
+def run_caffe2_model(init_net, predict_net, inputs):


Already has one here: https://github.com/onnx/onnx-caffe2/blob/master/onnx_caffe2/helper.py#L56

bddppq · 2017-11-17T00:18:44Z

onnx_caffe2/pytorch_caffe2.py

+
+
+def run_caffe2_benchmark(init_net, predict_net, warmup_iters, main_iters, layer_details):
+    workspace.ResetWorkspace()


Don't directly use caffe2.python.workspace, use onnx_caffe2.workspace.Workspace instead.

bddppq · 2017-11-17T00:19:17Z

onnx_caffe2/pytorch_caffe2.py

+    return init_net, predict_net
+
+
+def load_caffe2_net(file):


Maybe move this into helper.py

bddppq · 2017-11-17T00:19:29Z

onnx_caffe2/pytorch_caffe2.py

+    return net
+
+
+def save_caffe2_net(net, file, output_txt=False):


bddppq · 2017-11-17T00:28:42Z

onnx_caffe2/pytorch_caffe2.py

+                                             pytorch_out, expected_decimal)
+    log.info("The converted Caffe2 model achieves {}-decimal precision."
+                 .format(expected_decimal))
+    if not compare_performance:


Split this into a separate benchmark/profile function

bddppq · 2017-11-17T00:32:44Z

onnx_caffe2/pytorch_caffe2.py

+        return init_net, predict_net
+
+    log.info("Starting benchmarking PyTorch.")
+    for _i in range(warmup_iters):


May be put these into a run_pytorch_benchmark function?

houseroad · 2017-11-17T02:12:40Z

Refactoring the code, will move most of the functions to onnx_caffe2/helper.py. And move the example to the tutorial repo.

dzhulgakov · 2017-11-18T01:06:35Z

onnx_caffe2/helper.py


    ws.RunNetOnce(predict_net)

    output_names = predict_net.external_output
    output_values = [ws.FetchBlob(name) for name in output_names]
    return ws, namedtupledict('Outputs', output_names)(*output_values)
+
+
+def name_inputs(onnx_model, inputs):


you should have the names of blobs in predict_net.external_input. So maybe just pass the list directly to c2_native_run_net?

init_net contains the fake input. So the assertion len(uninitialized) == len(inputs) fails. So it's better to pass a dict.

What I meant is to accept the list directly in c2_native_run_net() and put this code there

dzhulgakov · 2017-11-18T01:07:50Z

onnx_caffe2/helper.py

+def benchmark_pytorch_model(model, inputs, training=False, warmup_iters=3,
+                            main_iters=10, verbose=False):
+    for _i in range(warmup_iters):
+        ts = time.time()


no need for time in warmup

Nice catch.

dzhulgakov · 2017-11-18T01:08:05Z

onnx_caffe2/helper.py

+        ts = time.time()
+        model(*inputs)
+        te = time.time()
+        total_pytorch_time = te - ts + total_pytorch_time


dzhulgakov · 2017-11-18T01:08:15Z

onnx_caffe2/helper.py

+        model(*inputs)
+        te = time.time()
+        total_pytorch_time = te - ts + total_pytorch_time
+    log.info("The PyTorch model execution time per iter is {} milliseconds, "


also return time?

Good point!

dzhulgakov · 2017-11-18T01:08:57Z

examples/pytorch_to_caffe2.py

+init_net = load_caffe2_net(init_file)
+predict_net = load_caffe2_net(predict_file)
+
+# Prepare the inputs for Caffe2.


this should be handled by passing option to Caffe2Backend

dzhulgakov

Looks good, ship it!

dzhulgakov · 2017-11-23T03:21:55Z

onnx_caffe2/helper.py


    ws.RunNetOnce(predict_net)

    output_names = predict_net.external_output
    output_values = [ws.FetchBlob(name) for name in output_names]
    return ws, namedtupledict('Outputs', output_names)(*output_values)
+
+
+def name_inputs(onnx_model, inputs):


What I meant is to accept the list directly in c2_native_run_net() and put this code there

dzhulgakov · 2017-11-23T03:22:31Z

onnx_caffe2/helper.py

+        ws.RunNetOnce(init_net)
+    ws.CreateNet(predict_net)
+    results = ws.BenchmarkNet(predict_net.name, warmup_iters, main_iters, layer_details)
+    return results[0]


add del ws to free up memory explicitly

Add an example python file to demonstrate how to convert PyTorch models to Caffe2.

houseroad requested review from jamesr66a, bddppq and dzhulgakov November 17, 2017 00:01

bddppq reviewed Nov 17, 2017

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houseroad changed the title ~~Create library for converting pytorch to caffe2 and examples~~ [WIP] Create library for converting pytorch to caffe2 and examples Nov 17, 2017

houseroad force-pushed the master branch from 9a89821 to a576335 Compare November 17, 2017 06:24

houseroad changed the title ~~[WIP] Create library for converting pytorch to caffe2 and examples~~ Create library for converting pytorch to caffe2 and examples Nov 17, 2017

houseroad force-pushed the master branch from a576335 to 087ba4c Compare November 17, 2017 06:32

dzhulgakov reviewed Nov 18, 2017

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dzhulgakov approved these changes Nov 23, 2017

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houseroad added 3 commits November 23, 2017 09:50

Add helper functions for pytorch->caffe2 conversion, and benchmark.

0d8278b

Add an example python file to demonstrate how to convert PyTorch models to Caffe2.

Update the example

876057e

Merge name_inuts() into c2_native_run_net

781b5ef

houseroad force-pushed the master branch 2 times, most recently from 06d305e to 60baedf Compare November 25, 2017 03:44

Fix the pad order problem

afba6aa

houseroad force-pushed the master branch from 60baedf to afba6aa Compare November 25, 2017 04:20

houseroad added 2 commits November 27, 2017 12:42

Merge branch 'master' into master

ce644a9

Merge branch 'master' into master

bc73b1e

houseroad merged commit db94c12 into onnx:master Nov 27, 2017

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Create library for converting pytorch to caffe2 and examples #69

Create library for converting pytorch to caffe2 and examples #69

houseroad commented Nov 17, 2017

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houseroad commented Nov 17, 2017

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dzhulgakov Nov 23, 2017

dzhulgakov Nov 23, 2017

		log = logging.getLogger(__name__)


		def run_caffe2_model(init_net, predict_net, inputs):



		def run_caffe2_benchmark(init_net, predict_net, warmup_iters, main_iters, layer_details):
		workspace.ResetWorkspace()

Create library for converting pytorch to caffe2 and examples #69

Create library for converting pytorch to caffe2 and examples #69

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houseroad commented Nov 17, 2017

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