From f2d7787e5736386761b47722bb3a4aecf387cc86 Mon Sep 17 00:00:00 2001
From: Lianmin Zheng <mercy_zheng@sjtu.edu.cn>
Date: Tue, 30 Oct 2018 19:20:53 -0700
Subject: [PATCH] [AUTOTVM] Misc fix to document and style (#2035)
---
apps/benchmark/util.py | 2 +-
docs/install/from_source.rst | 13 ++++---
python/tvm/autotvm/measure/measure_methods.py | 4 +-
python/tvm/autotvm/record.py | 6 +--
python/tvm/autotvm/task/dispatcher.py | 39 +++++++------------
python/tvm/relay/testing/init.py | 5 ++-
python/tvm/target.py | 6 +--
7 files changed, 36 insertions(+), 39 deletions(-)
diff --git a/apps/benchmark/util.py b/apps/benchmark/util.py
index bdf47dd66..ac732d794 100644
--- a/apps/benchmark/util.py
+++ b/apps/benchmark/util.py
@@ -34,7 +34,7 @@ def get_network(name, batch_size, dtype='float32'):
elif name == 'mobilenet_v2':
net, params = nnvm.testing.mobilenet_v2.get_workload(batch_size=batch_size, dtype=dtype)
elif name == 'inception_v3':
- input_shape = (1, 3, 299, 299)
+ input_shape = (batch_size, 3, 299, 299)
net, params = nnvm.testing.inception_v3.get_workload(batch_size=batch_size, dtype=dtype)
elif "resnet" in name:
n_layer = int(name.split('-')[1])
diff --git a/docs/install/from_source.rst b/docs/install/from_source.rst
index 2228e92b2..84bfa3c63 100644
--- a/docs/install/from_source.rst
+++ b/docs/install/from_source.rst
@@ -124,13 +124,15 @@ TVM package
~~~~~~~~~~~
The python package is located at `tvm/python`
-There are several ways to install the package:
+There are two ways to install the package:
-1. Set the environment variable `PYTHONPATH` to tell python where to find
+Method 1
+ This method is **recommended for developers** who may change the codes.
+
+ Set the environment variable `PYTHONPATH` to tell python where to find
the library. For example, assume we cloned `tvm` on the home directory
`~`. then we can added the following line in `~/.bashrc`.
- It is **recommended for developers** who may change the codes.
- The changes will be immediately reflected once you pulled the code and rebuild the project (no need to call ``setup`` again)
+ The changes will be immediately reflected once you pull the code and rebuild the project (no need to call ``setup`` again)
.. code:: bash
@@ -138,7 +140,8 @@ There are several ways to install the package:
export PYTHONPATH=$TVM_HOME/python:$TVM_HOME/topi/python:$TVM_HOME/nnvm/python:${PYTHONPATH}
-2. Install tvm python bindings by `setup.py`:
+Method 2
+ Install tvm python bindings by `setup.py`:
.. code:: bash
diff --git a/python/tvm/autotvm/measure/measure_methods.py b/python/tvm/autotvm/measure/measure_methods.py
index 975faf71b..802abe019 100644
--- a/python/tvm/autotvm/measure/measure_methods.py
+++ b/python/tvm/autotvm/measure/measure_methods.py
@@ -551,7 +551,9 @@ def check_remote(target, device_key, host=None, port=None, priority=100, timeout
"""
def _check():
remote = request_remote(device_key, host, port, priority)
- remote.context(str(target))
+ ctx = remote.context(str(target))
+ while not ctx.exist: # wait until we get an available device
+ pass
t = threading.Thread(target=_check,)
t.start()
t.join(timeout)
diff --git a/python/tvm/autotvm/record.py b/python/tvm/autotvm/record.py
index 910f7595a..3135e5c58 100644
--- a/python/tvm/autotvm/record.py
+++ b/python/tvm/autotvm/record.py
@@ -252,13 +252,13 @@ Usage:
This record executable module has three modes.
* Print log file in readable format
-e.g. python -m autotvm.record --mode read --i collect_conv.log --begin 0 --end 5 --ir --code
+e.g. python -m tvm.autotvm.record --mode read --i collect_conv.log --begin 0 --end 5 --ir --code
* Extract history best from a large log file
-e.g. python -m autotvm.record --mode pick --i collect.log
+e.g. python -m tvm.autotvm.record --mode pick --i collect.log
* Split a log file into separate files, each of which contains only a single wkl
-e.g. python -m autotvm.record --mode split --i collect.log
+e.g. python -m tvm.autotvm.record --mode split --i collect.log
"""
if __name__ == '__main__':
parser = argparse.ArgumentParser()
diff --git a/python/tvm/autotvm/task/dispatcher.py b/python/tvm/autotvm/task/dispatcher.py
index fd91d60e7..c5464f94f 100644
--- a/python/tvm/autotvm/task/dispatcher.py
+++ b/python/tvm/autotvm/task/dispatcher.py
@@ -292,17 +292,13 @@ class ApplyHistoryBest(DispatchContext):
best_by_targetkey[key] = (inp, res)
# use model as key to build best map
- for opt in inp.target.options:
- if opt.startswith("-model"):
- model = opt[7:]
- key = (model, inp.task.workload)
- if key not in best_by_model:
- best_by_model[key] = (inp, res)
- else:
- _, other_res = best_by_model[key]
- if np.mean(other_res.costs) > np.mean(res.costs):
- best_by_model[key] = (inp, res)
- break
+ key = (inp.target.model, inp.task.workload)
+ if key not in best_by_model:
+ best_by_model[key] = (inp, res)
+ else:
+ _, other_res = best_by_model[key]
+ if np.mean(other_res.costs) > np.mean(res.costs):
+ best_by_model[key] = (inp, res)
logger.debug("Finish loading %d records", counter)
@@ -313,14 +309,11 @@ class ApplyHistoryBest(DispatchContext):
" above the dispatcher call. So does other target. ")
# first try matching by model
- for opt in target.options:
- if opt.startswith("-model"):
- model = opt[7:]
- key = (model, workload)
- if key in self._best_user_defined:
- return self._best_user_defined[key]
- if key in self.best_by_model:
- return self.best_by_model[key][0].config
+ key = (target.model, workload)
+ if key in self._best_user_defined:
+ return self._best_user_defined[key]
+ if key in self.best_by_model:
+ return self.best_by_model[key][0].config
# then try matching by target key
for k in target.keys:
@@ -333,11 +326,9 @@ class ApplyHistoryBest(DispatchContext):
return None
def update(self, target, workload, cfg):
- for opt in target.options:
- if opt.startswith("-model"):
- model = opt[7:]
- key = (model, workload)
- self._best_user_defined[key] = cfg
+ model = target.model
+ key = (model, workload)
+ self._best_user_defined[key] = cfg
for k in target.keys:
key = (k, workload)
diff --git a/python/tvm/relay/testing/init.py b/python/tvm/relay/testing/init.py
index fdbde9d28..7f92b539a 100644
--- a/python/tvm/relay/testing/init.py
+++ b/python/tvm/relay/testing/init.py
@@ -1,7 +1,8 @@
"""Initializer of parameters."""
+import numpy as np
+
import tvm
from tvm import relay
-import numpy as np
class Initializer(object):
"""The base class of an initializer."""
@@ -103,7 +104,7 @@ class Xavier(Initializer):
raise ValueError("Incorrect factor type")
# Hack for mobilenet, because there is less connectivity
if "depthwise" in name:
- factor = 3 * 3
+ factor = hw_scale
scale = np.sqrt(self.magnitude / factor)
if self.rnd_type == "uniform":
arr[:] = np.random.uniform(-scale, scale, size=arr.shape)
diff --git a/python/tvm/target.py b/python/tvm/target.py
index b3a9086e7..75f82743f 100644
--- a/python/tvm/target.py
+++ b/python/tvm/target.py
@@ -419,7 +419,7 @@ def intel_graphics(model='unknown', options=None):
return _api_internal._TargetCreate("opencl", *opts)
-def opengl(options=None):
+def opengl(model='unknown', options=None):
"""Returns a OpenGL target.
Parameters
@@ -427,8 +427,8 @@ def opengl(options=None):
options : str or list of str
Additional options
"""
- options = _merge_opts([], options)
- return _api_internal._TargetCreate("opengl", *options)
+ opts = _merge_opts(["-model=%s" % model], options)
+ return _api_internal._TargetCreate("opengl", *opts)
def arm_cpu(model='unknown', options=None):
--
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