[v1.6] Fix the monitor_callback invalid issue during calibration with…

… variable input shapes (#18632) (#18703)

* Fix the monitor_callback invalid issue during calibration with variable input shapes

* retrigger CI

* Add UT for monitor check and disable codecov

Co-authored-by: Tao Lv <[email protected]>

.codecov.yml

@@ -4,6 +4,9 @@ codecov:
  require_ci_to_pass: yes
 
 coverage:
+ status:
+ project: off
+ patch: off
  precision: 2
  round: down
  range: "70...100"

python/mxnet/executor.py

@@ -79,6 +79,7 @@ def __init__(self, handle, symbol, ctx, grad_req, group2ctx):
  self._aux_dict = None
  self._output_dict = None
  self._monitor_callback = None
+ self._monitor_all = None
  self._ctx = copy.deepcopy(ctx)
  self._grad_req = copy.deepcopy(grad_req)
  self._group2ctx = copy.deepcopy(group2ctx)
@@ -253,6 +254,7 @@ def set_monitor_callback(self, callback, monitor_all=False):
  """
  cb_type = ctypes.CFUNCTYPE(None, ctypes.c_char_p, NDArrayHandle, ctypes.c_void_p)
  self._monitor_callback = cb_type(_monitor_callback_wrapper(callback))
+ self._monitor_all = monitor_all
  check_call(_LIB.MXExecutorSetMonitorCallbackEX(
  self.handle,
  self._monitor_callback,
@@ -477,6 +479,13 @@ def reshape(self, partial_shaping=False, allow_up_sizing=False, **kwargs):
  executor.arg_arrays = arg_arrays
  executor.grad_arrays = grad_arrays
  executor.aux_arrays = aux_arrays
+ if (self._monitor_callback is not None) and (self._monitor_all is not None):
+ # rebind callback to the new executor if the callback is valid
+ check_call(_LIB.MXExecutorSetMonitorCallbackEX(
+ handle,
+ self._monitor_callback,
+ None,
+ ctypes.c_int(self._monitor_all)))
  return executor
 
  def debug_str(self):

tests/python/unittest/test_operator.py

@@ -8364,6 +8364,59 @@ def get_output_names_callback(name, arr):
  check_name(us_sym, ['data', 'pooling_data', 'pooling_output'])
  del os.environ['MXNET_SUBGRAPH_BACKEND']
 
+@with_seed()
+def test_monitor_with_variable_input_shape():
+ output = {}
+
+ def get_output_min_callback(name, arr):
+ name = py_str(name)
+ handle = ctypes.cast(arr, NDArrayHandle)
+ arr = NDArray(handle, writable=False)
+ min_val = mx.ndarray.min(arr).asscalar()
+ if name in output:
+ output[name] = min(output[name], min_val)
+ else:
+ output[name] = min_val
+
+ def check_result(output, names):
+ assert len(output) > 0
+ for k, v in output.items():
+ assert k in names
+ assert v is not None
+
+ is_windows = sys.platform.startswith('win')
+ if (is_windows):
+ # Windows doesn't support set environment variable on the fly, so disable it for now
+ pass
+ else:
+ # Disable subgraph in case subgraph will replace symbol
+ os.environ['MXNET_SUBGRAPH_BACKEND'] = "NONE"
+
+ batch_size = 1
+ op_name = 'conv'
+ dshape = (batch_size, 3, 10, 10)
+ data = mx.sym.Variable('data', shape=dshape)
+ sym = mx.sym.Convolution(data, kernel=(1, 1), num_filter=1, name=op_name)
+
+ mod = mx.module.Module(symbol=sym, label_names=None)
+ mod.bind(for_training=False, data_shapes=[('data', dshape)])
+ mod.init_params()
+ mod._exec_group.execs[0].set_monitor_callback(get_output_min_callback, monitor_all=True)
+
+ new_dshape = dshape[:-1] + (dshape[-1] + 4,)
+ new_data = mx.nd.random.uniform(shape=new_dshape)
+ new_data = mx.io.NDArrayIter(data=new_data, batch_size=batch_size)
+ new_data = DummyIter(new_data)
+
+ for batch in new_data:
+ mod.forward(data_batch=batch, is_train=False)
+ mx.nd.waitall()
+ break
+
+ name_list = ['data', 'conv_data', 'conv_weight', 'conv_bias', 'conv_output']
+ check_result(output, name_list)
+ del os.environ['MXNET_SUBGRAPH_BACKEND']
+
 @with_seed()
 @unittest.skip("test fails intermittently. temporarily disabled till it gets fixed. tracked at https://github.com/apache/incubator-mxnet/issues/13915")
 def test_activation():