flake8 fixes

theano/compile/debugmode.py

@@ -544,8 +544,9 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
                          we don't print anything below it.
     :param scan_ops: Scan ops in the graph will be added inside this list
                      for later printing purposes.
-    :param scan_inner_to_outer_inputs: a dictionary mapping a scan ops inner function
-    inputs to the scan op inputs (outer inputs) for printing purposes.
+    :param scan_inner_to_outer_inputs: a dictionary mapping a scan ops
+    inner function inputs to the scan op inputs (outer inputs) for
+    printing purposes.
 
     """
     if depth == 0:
@@ -681,7 +682,8 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
                                       theano.scan_module.scan_op.Scan):
                             scan_ops.append(i)
 
-                    debugprint(i, new_prefix, depth=depth - 1, done=done,
+                    debugprint(
+                        i, new_prefix, depth=depth - 1, done=done,
                         print_type=print_type, file=file, order=order,
                         ids=ids, stop_on_name=stop_on_name,
                         prefix_child=new_prefix_child, scan_ops=scan_ops,
@@ -698,7 +700,8 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
                 outer_id_str = get_id_str(outer_r.owner)
             else:
                 outer_id_str = get_id_str(outer_r)
-            print('%s%s %s%s -> %s' % (prefix, r, id_str, type_str, outer_id_str), file=file)
+            print('%s%s %s%s -> %s' % (prefix, r, id_str, type_str,
+                                       outer_id_str), file=file)
         else:
             # this is an input variable
             id_str = get_id_str(r)

theano/printing.py

@@ -168,16 +168,17 @@ N.B.:
             inner_to_outer_inputs = \
                 dict([(inner_inputs[i], outer_inputs[o])
                       for i, o in
-                      s.owner.op.var_mappings['outer_inp_from_inner_inp'].items()])
+                      s.owner.op.var_mappings['outer_inp_from_inner_inp']
+                      .items()])
 
             print("", file=_file)
-            debugmode.debugprint(s, depth=depth, done=done,
+            debugmode.debugprint(
+                s, depth=depth, done=done,
                 print_type=print_type,
                 file=_file, ids=ids,
                 scan_ops=scan_ops,
                 stop_on_name=stop_on_name,
-                                 scan_inner_to_outer_inputs=
-                                 inner_to_outer_inputs)
+                scan_inner_to_outer_inputs=inner_to_outer_inputs)
             if hasattr(s.owner.op, 'fn'):
                 # If the op was compiled, print the optimized version.
                 outputs = s.owner.op.fn.maker.fgraph.outputs
@@ -189,14 +190,14 @@ N.B.:
                     if isinstance(i.owner.op, theano.scan_module.scan_op.Scan):
                         scan_ops.append(i)
 
-                debugmode.debugprint(r=i, prefix=new_prefix,
+                debugmode.debugprint(
+                    r=i, prefix=new_prefix,
                     depth=depth, done=done,
                     print_type=print_type, file=_file,
                     ids=ids, stop_on_name=stop_on_name,
                     prefix_child=new_prefix_child,
                     scan_ops=scan_ops,
-                                     scan_inner_to_outer_inputs=
-                                     inner_to_outer_inputs)
+                    scan_inner_to_outer_inputs=inner_to_outer_inputs)
 
     if file is _file:
         return file

theano/tests/test_printing.py

@@ -303,9 +303,10 @@ def test_scan_debugprint1():
      > |<TensorType(float64, vector)> [@Y] -> [@E]
      > |A_copy [@Z] -> [@N]"""
 
-    for truth,out in zip(expected_output.split("\n"), lines):
+    for truth, out in zip(expected_output.split("\n"), lines):
         assert truth.strip() == out.strip()
 
+
 def test_scan_debugprint2():
     coefficients = theano.tensor.vector("coefficients")
     x = tensor.scalar("x")
@@ -313,11 +314,14 @@ def test_scan_debugprint2():
     max_coefficients_supported = 10000
 
     # Generate the components of the polynomial
-    components, updates = theano.scan(fn=lambda coefficient, power, free_variable:
+    components, updates = theano.scan(fn=lambda coefficient, power,
+                                      free_variable:
                                       coefficient * (free_variable ** power),
                                       outputs_info=None,
-                                      sequences=[coefficients,
-                                                 theano.tensor.arange(max_coefficients_supported)],
+                                      sequences=[
+                                          coefficients,
+                                          theano.tensor.arange(
+                                              max_coefficients_supported)],
                                       non_sequences=x)
     # Sum them up
     polynomial = components.sum()
@@ -327,7 +331,7 @@ def test_scan_debugprint2():
     for line in output_str.split('\n'):
         lines += [line]
 
-    expected_output= """Sum{acc_dtype=float64} [@A] ''
+    expected_output = """Sum{acc_dtype=float64} [@A] ''
      |for{cpu,scan_fn} [@B] ''
        |Elemwise{minimum,no_inplace} [@C] ''
        | |Subtensor{int64} [@D] ''
@@ -365,7 +369,7 @@ def test_scan_debugprint2():
      >   |x_copy [@BA] -> [@W]
      >   |<TensorType(int16, scalar)> [@BB] -> [@U]"""
 
-    for truth,out in zip(expected_output.split("\n"), lines):
+    for truth, out in zip(expected_output.split("\n"), lines):
         assert truth.strip() == out.strip()
 
 
@@ -379,7 +383,8 @@ def test_scan_debugprint3():
     # compute A**k
     def compute_A_k(A, k):
         # Symbolic description of the result
-        result, updates = theano.scan(fn=lambda prior_result, A: prior_result * A,
+        result, updates = theano.scan(fn=lambda prior_result,
+                                      A: prior_result * A,
                                       outputs_info=tensor.ones_like(A),
                                       non_sequences=A,
                                       n_steps=k)
@@ -389,11 +394,15 @@ def test_scan_debugprint3():
         return A_k
 
     # Generate the components of the polynomial
-    components, updates = theano.scan(fn=lambda coefficient, power, some_A, some_k:
-                                      coefficient * (compute_A_k(some_A, some_k) ** power),
+    components, updates = theano.scan(fn=lambda coefficient,
+                                      power, some_A, some_k:
+                                      coefficient *
+                                      (compute_A_k(some_A, some_k) ** power),
                                       outputs_info=None,
-                                      sequences=[coefficients,
-                                                 theano.tensor.arange(max_coefficients_supported)],
+                                      sequences=[
+                                          coefficients,
+                                          theano.tensor.arange(
+                                              max_coefficients_supported)],
                                       non_sequences=[A, k])
     # Sum them up
     polynomial = components.sum()
@@ -405,7 +414,7 @@ def test_scan_debugprint3():
     for line in output_str.split('\n'):
         lines += [line]
 
-    expected_output="""Sum{acc_dtype=float64} [@A] ''
+    expected_output = """Sum{acc_dtype=float64} [@A] ''
      |for{cpu,scan_fn} [@B] ''
        |Elemwise{minimum,no_inplace} [@C] ''
        | |Subtensor{int64} [@D] ''
@@ -478,7 +487,7 @@ def test_scan_debugprint3():
      > |<TensorType(float64, vector)> [@CC] -> [@BG]
      > |A_copy [@CD] -> [@BP]"""
 
-    for truth,out in zip(expected_output.split("\n"), lines):
+    for truth, out in zip(expected_output.split("\n"), lines):
         assert truth.strip() == out.strip()
 
 
@@ -490,7 +499,8 @@ def test_scan_debugprint4():
     a0 = theano.shared(numpy.arange(2))
     b0 = theano.shared(numpy.arange(2))
 
-    (a, b), _ = theano.scan(fn, outputs_info=[{'initial': a0, 'taps': [-2, -1]},
+    (a, b), _ = theano.scan(fn, outputs_info=[
+        {'initial': a0, 'taps': [-2, -1]},
         {'initial': b0, 'taps': [-2, -1]}],
                             n_steps=5)
 
@@ -551,11 +561,7 @@ def test_scan_debugprint4():
      >Elemwise{add,no_inplace} [@BC] ''
      >Elemwise{add,no_inplace} [@BF] ''"""
 
-    # output = "\n".join(lines)
-    # with open('output5.txt', 'w') as f:
-    #     f.write(output)
-
-    for truth,out in zip(expected_output.split("\n"), lines):
+    for truth, out in zip(expected_output.split("\n"), lines):
         assert truth.strip() == out.strip()
 
 
@@ -695,5 +701,5 @@ def test_scan_debugprint5():
     for{cpu,scan_fn} [@BP] ''
      >Elemwise{mul,no_inplace} [@CS] ''"""
 
-    for truth,out in zip(expected_output.split("\n"), lines):
+    for truth, out in zip(expected_output.split("\n"), lines):
         assert truth.strip() == out.strip()