Remove OrderedDict from tests/scan/test_basic

Author: Armavica

tests/scan/test_basic.py

@@ -13,7 +13,6 @@
 import pickle
 import shutil
 import sys
-from collections import OrderedDict
 from tempfile import mkdtemp
 
 import numpy as np
@@ -764,11 +763,9 @@ def test_output_padding(self):
         b = shared(np.random.default_rng(utt.fetch_seed()).random((5, 4)))
 
         def inner_func(a):
-            return a + 1, OrderedDict([(b, 2 * b)])
+            return a + 1, {b: 2 * b}
 
-        out, updates = scan(
-            inner_func, outputs_info=[OrderedDict([("initial", init_a)])], n_steps=1
-        )
+        out, updates = scan(inner_func, outputs_info=[{"initial": init_a}], n_steps=1)
         out = out[-1]
         assert out.type.ndim == a.type.ndim
         assert updates[b].type.ndim == b.type.ndim
@@ -934,7 +931,7 @@ def test_only_shared_no_input_no_output(self):
         state = shared(v_state, "vstate")
 
         def f_2():
-            return OrderedDict([(state, 2 * state)])
+            return {state: 2 * state}
 
         n_steps = iscalar("nstep")
         output, updates = scan(
@@ -968,7 +965,7 @@ def test_shared_updates(self):
         X = shared(np.array(1))
 
         out, updates = scan(
-            lambda: OrderedDict([(X, (X + 1))]),
+            lambda: {X: (X + 1)},
             outputs_info=[],
             non_sequences=[],
             sequences=[],
@@ -984,7 +981,7 @@ def test_shared_memory_aliasing_updates(self):
         y = shared(np.array(1))
 
         out, updates = scan(
-            lambda: OrderedDict([(x, x + 1), (y, x)]),
+            lambda: {x: x + 1, y: x},
             outputs_info=[],
             non_sequences=[],
             sequences=[],
@@ -1914,7 +1911,7 @@ def test_grad_numeric_shared(self):
         shared_var = shared(np.float32(1.0))
 
         def inner_fn():
-            return [], OrderedDict([(shared_var, shared_var + np.float32(1.0))])
+            return [], {shared_var: shared_var + np.float32(1.0)}
 
         _, updates = scan(
             inner_fn, n_steps=10, truncate_gradient=-1, go_backwards=False
@@ -2746,7 +2743,7 @@ def one_step(x_t, h_tm1, W):
 
         v1 = shared(np.ones(5, dtype=config.floatX))
         v2 = shared(np.ones((5, 5), dtype=config.floatX))
-        shapef = function([W], expr, givens=OrderedDict([(initial, v1), (inpt, v2)]))
+        shapef = function([W], expr, givens={initial: v1, inpt: v2})
         # First execution to cache n_steps
         shapef(np.ones((5, 5), dtype=config.floatX))
 
@@ -2755,7 +2752,7 @@ def one_step(x_t, h_tm1, W):
         f = function(
             [W, inpt],
             d_cost_wrt_W,
-            givens=OrderedDict([(initial, shared(np.zeros(5)))]),
+            givens={initial: shared(np.zeros(5))},
         )
 
         rval = np.asarray([[5187989] * 5] * 5, dtype=config.floatX)
@@ -2956,7 +2953,7 @@ def onestep(x, x_tm4):
 
         seq = matrix()
         initial_value = shared(np.zeros((4, 1), dtype=config.floatX))
-        outputs_info = [OrderedDict([("initial", initial_value), ("taps", [-4])]), None]
+        outputs_info = [{"initial": initial_value, "taps": [-4]}, None]
         results, updates = scan(fn=onestep, sequences=seq, outputs_info=outputs_info)
 
         f = function([seq], results[1])
@@ -2979,10 +2976,10 @@ def onestep(x, x_tm4):
 
         seq = matrix()
         initial_value = shared(np.zeros((4, 1), dtype=config.floatX))
-        outputs_info = [OrderedDict([("initial", initial_value), ("taps", [-4])]), None]
+        outputs_info = [{"initial": initial_value, "taps": [-4]}, None]
         results, _ = scan(fn=onestep, sequences=seq, outputs_info=outputs_info)
         sharedvar = shared(np.zeros((1, 1), dtype=config.floatX))
-        updates = OrderedDict([(sharedvar, results[0][-1:])])
+        updates = {sharedvar: results[0][-1:]}
 
         f = function([seq], results[1], updates=updates)