diagnose option: get_entry to print a whole row (#11308)

Summary:
Pull Request resolved: #11308

Pull Request resolved: #11299

Reviewed By: xianjiec

Differential Revision: D9652844

fbshipit-source-id: 650d550317bfbed0c1f25ae7d74286cfc7c3ac70

caffe2/python/modeling/get_entry_from_blobs.py

@@ -33,21 +33,23 @@ class GetEntryFromBlobs(NetModifier):
         blobs: list of blobs to get entry from
         logging_frequency: frequency for printing entry values to logs
         i1, i2: the first, second dimension of the blob. (currently, we assume
-        the blobs to be 2-dimensional blobs)
+        the blobs to be 2-dimensional blobs). When i2 = -1, print all entries
+        in blob[i1]
     """
 
     def __init__(self, blobs, logging_frequency, i1=0, i2=0):
         self._blobs = blobs
         self._logging_frequency = logging_frequency
         self._i1 = i1
         self._i2 = i2
-        self._field_name_suffix = '_{0}_{1}'.format(i1, i2)
+        self._field_name_suffix = '_{0}_{1}'.format(i1, i2) if i2 >= 0 \
+            else '_{0}_all'.format(i1)
 
     def modify_net(self, net, init_net=None, grad_map=None, blob_to_device=None,
                     modify_output_record=False):
 
         i1, i2 = [self._i1, self._i2]
-        if i1 < 0 or i2 < 0:
+        if i1 < 0:
             raise ValueError('index is out of range')
 
         for blob_name in self._blobs:
@@ -57,16 +59,20 @@ def modify_net(self, net, init_net=None, grad_map=None, blob_to_device=None,
                     blob, net.Name()))
 
             blob_i1 = net.Slice([blob], starts=[i1, 0], ends=[i1 + 1, -1])
-            blob_i1_i2 = net.Slice([blob_i1],
-                            net.NextScopedBlob(prefix=blob + '_{0}_{1}'.format(i1, i2)),
-                            starts=[0, i2], ends=[-1, i2 + 1])
+            if self._i2 == -1:
+                blob_i1_i2 = net.Copy([blob_i1],
+                    [net.NextScopedBlob(prefix=blob + '_{0}_all'.format(i1))])
+            else:
+                blob_i1_i2 = net.Slice([blob_i1],
+                    net.NextScopedBlob(prefix=blob + '_{0}_{1}'.format(i1, i2)),
+                    starts=[0, i2], ends=[-1, i2 + 1])
 
             if self._logging_frequency >= 1:
                 net.Print(blob_i1_i2, [], every_n=self._logging_frequency)
 
             if modify_output_record:
                 output_field_name = str(blob) + self._field_name_suffix
-                output_scalar = schema.Scalar((np.float, (1,)), blob_i1_i2)
+                output_scalar = schema.Scalar((np.float), blob_i1_i2)
 
                 if net.output_record() is None:
                     net.set_output_record(

caffe2/python/modeling/get_entry_from_blobs_test.py

@@ -60,7 +60,7 @@ def test_get_entry_from_blobs_modify_output_record(self):
 
         # no operator name set, will use default
         brew.fc(model, fc1, "fc2", dim_in=4, dim_out=4)
-        i1, i2 = np.random.randint(4, size=2)
+        i1, i2 = np.random.randint(4), np.random.randint(5) - 1
         net_modifier = GetEntryFromBlobs(
             blobs=['fc1_w', 'fc2_w'],
             logging_frequency=10,
@@ -74,10 +74,18 @@ def test_get_entry_from_blobs_modify_output_record(self):
         workspace.RunNetOnce(model.net)
 
         fc1_w = workspace.FetchBlob('fc1_w')
-        fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2))
+        if i2 < 0:
+            fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_all'.format(i1))
+        else:
+            fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2))
 
-        self.assertEqual(fc1_w_entry.size, 1)
-        self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2])
+        if i2 < 0:
+            self.assertEqual(fc1_w_entry.size, 4)
+            for j in range(4):
+                self.assertEqual(fc1_w_entry[0][j], fc1_w[i1][j])
+        else:
+            self.assertEqual(fc1_w_entry.size, 1)
+            self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2])
 
         assert 'fc1_w' + net_modifier.field_name_suffix() in\
             model.net.output_record().field_blobs(),\