Skip to content

[CI] Update GPU image for oneflow v0.7 #11085

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Apr 21, 2022
Merged

[CI] Update GPU image for oneflow v0.7 #11085

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions Jenkinsfile
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -45,12 +45,12 @@
// 'python3 jenkins/generate.py'
// Note: This timestamp is here to ensure that updates to the Jenkinsfile are
// always rebased on main before merging:
// Generated at 2022-04-19T10:04:53.134656
// Generated at 2022-04-21T08:18:57.400427

import org.jenkinsci.plugins.pipeline.modeldefinition.Utils
// NOTE: these lines are scanned by docker/dev_common.sh. Please update the regex as needed. -->
ci_lint = 'tlcpack/ci-lint:v0.71'
ci_gpu = 'tlcpack/ci-gpu:v0.85'
ci_gpu = 'tlcpack/ci-gpu:v0.86'
ci_cpu = 'tlcpack/ci-cpu:v0.84'
ci_wasm = 'tlcpack/ci-wasm:v0.73'
ci_i386 = 'tlcpack/ci-i386:v0.77'
Expand Down
2 changes: 1 addition & 1 deletion jenkins/Jenkinsfile.j2
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,7 @@ import org.jenkinsci.plugins.pipeline.modeldefinition.Utils

// NOTE: these lines are scanned by docker/dev_common.sh. Please update the regex as needed. -->
ci_lint = 'tlcpack/ci-lint:v0.71'
ci_gpu = 'tlcpack/ci-gpu:v0.85'
ci_gpu = 'tlcpack/ci-gpu:v0.86'
ci_cpu = 'tlcpack/ci-cpu:v0.84'
ci_wasm = 'tlcpack/ci-wasm:v0.73'
ci_i386 = 'tlcpack/ci-i386:v0.77'
Expand Down
58 changes: 27 additions & 31 deletions python/tvm/relay/frontend/oneflow.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -274,8 +274,8 @@ class Conv(OneFlowOpConverter):
@classmethod
def _impl_v1(cls, inputs, attrs, params):
# The kernel is imported from model_dir_path, without the ".weight" logo, etc.
# The data is obtained through the graph, its op contains "-input_"
in_names = ["-input_"]
# The data is obtained through the graph, its op contains "_input."
in_names = ["_input."]
kernel_names = [".weight"]
for i in inputs:
IN_NAMES = any(x in str(i) for x in in_names)
Expand Down Expand Up @@ -335,7 +335,7 @@ class ConvTranspose(OneFlowOpConverter):

@classmethod
def _impl_v1(cls, inputs, attrs, params):
in_names = ["-input_"]
in_names = ["_input."]
kernel_names = [".weight"]
for i in inputs:
IN_NAMES = any(x in str(i) for x in in_names)
Expand Down Expand Up @@ -470,7 +470,7 @@ def _impl_v1(cls, inputs, attrs, params):
# sort the inputs
sorted_inputs = copy.deepcopy(inputs)
for i in inputs:
IN_NAMES = "-input_" in str(i)
IN_NAMES = "_input." in str(i)
if IN_NAMES:
sorted_inputs[0] = i
elif "weight" in str(i) and not IN_NAMES:
Expand Down Expand Up @@ -521,7 +521,7 @@ def _impl_v1(cls, inputs, attrs, params):
assert len(inputs) == 2, "Gemm op take 2 inputs, {} given".format(len(inputs))
# Similar to 'class Conv'
true_names = ["weight"]
false_names = ["-input_"]
false_names = ["_input."]
for i in inputs:
T_NAMES = any(x in str(i) for x in true_names)
F_NAMES = any(x in str(i) for x in false_names)
Expand Down Expand Up @@ -607,7 +607,7 @@ def _impl_v1(cls, inputs, attrs, params):
axis = int(attrs.get("axis", 0))

true_names = ["weight", "bias"]
false_names = ["-input_"]
false_names = ["_input."]

for i in inputs:
T_NAMES = any(x in str(i) for x in true_names)
Expand Down Expand Up @@ -665,7 +665,7 @@ def _impl_v1(cls, inputs, attrs, params):

for i in inputs:
T_NAMES = any([x in str(i) for x in beta_names])
if T_NAMES and "-input_" not in str(i):
if T_NAMES and "_input." not in str(i):
input_b = i
else:
input_a = i
Expand Down Expand Up @@ -923,7 +923,7 @@ class PReLU(OneFlowOpConverter):
def _impl_v1(cls, inputs, attrs, params):
assert len(inputs) == 2, "PReLU need 2 inputs, but {} given".format(len(inputs))
for i in inputs:
if "-input_" in str(i):
if "_input." in str(i):
prelu_a = i
else:
prelu_b = i
Expand Down Expand Up @@ -1376,7 +1376,7 @@ def deal_with_input_convert(
if node_input not in _nodes:
if (
node_path not in _input_path_2_name
or "-input_" in node_input
or "_input." in node_input
or "FreeEagerTensor" in node_input
):
_nodes[node_input] = new_var(
Expand Down Expand Up @@ -1430,8 +1430,8 @@ class OneflowGraph(object):
node name:
1. param: m.layer4.1.bn1.weight / ...
2. buffer: m.layer4.1.bn1.running_mean / ...
3. node inputs: m.layer4.1.bn1-input_0
4. node outputs: m.layer4.1.bn1-output_0
3. node inputs: m.layer4.1.bn1_input.0
4. node outputs: m.layer4.1.bn1_output.0
"""

def __init__(self, shape, dtype, nodes, model_dir_path):
Expand Down Expand Up @@ -1521,16 +1521,19 @@ def _parse_input(self, node, model_dir_path):

def _parse_output(self, op_name, outputs, cnt_init=0):
"""
o: m.classifier.1-output_xxx
o: m.classifier.1_output.xxx
new_o: m.classifier.1-conv2d_0
"_"+new_o is in self._shape
"_"+new_o_xxx is in self._shape
"""
for o in outputs:
if "-output_" not in o:
new_o = o.replace("-" + op_name, "-output")
new_o = new_o.replace("_" + new_o.split("_")[-1], "_0")
self._shape[o] = self._shape["_" + new_o]
self._dtype[o] = self._dtype["_" + new_o]
if "_output." not in o:
new_o = o.replace("-" + op_name, "_output")
new_o = new_o.replace("-" + new_o.split("-")[-1], ".0")
for k in self._shape.keys():
if new_o in k:
self._shape[o] = self._shape[k]
self._dtype[o] = self._dtype[k]
break
elif len(outputs) > 1:
outputs.remove(o)
if op_name.lower() == "dropout":
Expand All @@ -1557,15 +1560,15 @@ def from_oneflow(self, nodes, model_dir_path, freeze_params=True, user_input=Non
If freeze_params is True,
the computational graph input is the input of the first layer of the network,
which cannot be specified by the user, e.g.
Default input is: %v_ResNetGraph_0-input_0: Tensor[(1, 3, 224, 224), float32]
User-defined input is: %_0-input_0: Tensor[(1, 3, 640, 480), float32]
Default input is: %v_ResNetGraph_0_input.0: Tensor[(1, 3, 224, 224), float32]
User-defined input is: %_0_input.0: Tensor[(1, 3, 640, 480), float32]
If freeze_params is on, then conv1-in will be the graph input, not Input_0
user_input: dict
User-defined input information for the graph
{
node1_name:
{
'name': node1_name, # str, like "%v_ResNetGraph_0-input_0"
'name': node1_name, # str, like "%v_ResNetGraph_0_input.0"
'shape': node1_shape, # tuple
'dtype': node1_dtype # str, like "float32"
}
Expand All @@ -1584,9 +1587,9 @@ def from_oneflow(self, nodes, model_dir_path, freeze_params=True, user_input=Non
# step 1: get the graph input
if not freeze_params:
for node_init_name in user_input:
if "-input_" not in node_init_name:
if "_input." not in node_init_name:
raise KeyError(
"user_input['name'] should contain '-input_' "
"user_input['name'] should contain '_input.' "
+ "to let program know that this is input node"
)
self._nodes[node_init_name] = new_var(
Expand Down Expand Up @@ -1693,19 +1696,12 @@ def from_oneflow(self, nodes, model_dir_path, freeze_params=True, user_input=Non
nodes = {v: k for k, v in self._nodes.items()}
free_vars = [nodes[var] for var in free_vars]

# step 6: make sure the '-input_0' is the first in self._inputs
# step 6: make sure the '_input.0' is the first in self._inputs
for free_var in free_vars:
if free_var not in self._inputs:
self._inputs[free_var] = self._nodes[free_var]

input_names = list(self._inputs.keys())
for i, _ in enumerate(input_names):
if i != 0 and "-input_0" in input_names[i]:
str_buffer = copy.deepcopy(input_names[i])
del input_names[i]
input_names.insert(0, str_buffer)
break

for input_name in input_names:
if input_name in self._inputs:
self._sort_inputs[input_name] = self._inputs[input_name]
Expand Down