def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilon=1e-04, name='Adam'): self.name = name self.t = _base.Variable(_sym.zeros(shape=[1]), name+'_t') self.learning_rate = learning_rate self.beta1 = beta1 self.beta2 = beta2 self.epsilon = epsilon self.m = [] self.v = []
def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilon=1e-04, name='Adam'): self.name = name self.t = _base.Variable(_sym.zeros(shape=[1]), name + '_t') self.learning_rate = learning_rate self.beta1 = beta1 self.beta2 = beta2 self.epsilon = epsilon self.m = [] self.v = []
def test_full(): shape = (3, 4, 5) value = 7 dtype = "float32" for target, ctx in ctx_list(): data = sym.Variable("data", dtype=dtype) # full_like s = sym.full_like(data=data, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target, {"data": shape}) m = graph_runtime.create(graph, lib, ctx) m.run(data=np.random.uniform(size=shape).astype(dtype)) out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) np.testing.assert_allclose(out.asnumpy(), np.full(shape, fill_value=value, dtype=dtype), atol=1e-5, rtol=1e-5) # ones_like s = sym.ones_like(data=data, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target, {"data": shape}) m = graph_runtime.create(graph, lib, ctx) m.run(data=np.random.uniform(size=shape).astype(dtype)) out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) np.testing.assert_allclose(out.asnumpy(), np.full(shape, fill_value=1, dtype=dtype), atol=1e-5, rtol=1e-5) # zeros_like s = sym.zeros_like(data=data, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target, {"data": shape}) m = graph_runtime.create(graph, lib, ctx) m.run(data=np.random.uniform(size=shape).astype(dtype)) out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) np.testing.assert_allclose(out.asnumpy(), np.full(shape, fill_value=0, dtype=dtype), atol=1e-5, rtol=1e-5) # full s = sym.full(shape=shape, dtype=dtype, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target) m = graph_runtime.create(graph, lib, ctx) m.run() out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) np.testing.assert_allclose(out.asnumpy(), np.full(shape, fill_value=value, dtype=dtype), atol=1e-5, rtol=1e-5) # ones s = sym.ones(shape=shape, dtype=dtype, name="s") graph, lib, _ = nnvm.compiler.build(s, target) m = graph_runtime.create(graph, lib, ctx) m.run() out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) np.testing.assert_allclose(out.asnumpy(), np.full(shape, fill_value=1, dtype=dtype), atol=1e-5, rtol=1e-5) # zeros s = sym.zeros(shape=shape, dtype=dtype, name="s") graph, lib, _ = nnvm.compiler.build(s, target) m = graph_runtime.create(graph, lib, ctx) m.run() out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) np.testing.assert_allclose(out.asnumpy(), np.full(shape, fill_value=0, dtype=dtype), atol=1e-5, rtol=1e-5)
def zeros(shape): return symbol.zeros(shape=shape)
def test_full(): shape = (3, 4, 5) value = 7 dtype = "float32" for target, ctx in ctx_list(): data = sym.Variable("data", dtype=dtype) # full_like s = sym.full_like(data=data, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target, {"data": shape}) m = graph_runtime.create(graph, lib, ctx) m.run(data=np.random.uniform(size=shape).astype(dtype)) out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) tvm.testing.assert_allclose( out.asnumpy(), np.full(shape, fill_value=value, dtype=dtype), atol=1e-5, rtol=1e-5) # ones_like s = sym.ones_like(data=data, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target, {"data": shape}) m = graph_runtime.create(graph, lib, ctx) m.run(data=np.random.uniform(size=shape).astype(dtype)) out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) tvm.testing.assert_allclose( out.asnumpy(), np.full(shape, fill_value=1, dtype=dtype), atol=1e-5, rtol=1e-5) # zeros_like s = sym.zeros_like(data=data, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target, {"data": shape}) m = graph_runtime.create(graph, lib, ctx) m.run(data=np.random.uniform(size=shape).astype(dtype)) out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) tvm.testing.assert_allclose( out.asnumpy(), np.full(shape, fill_value=0, dtype=dtype), atol=1e-5, rtol=1e-5) # full s = sym.full(shape=shape, dtype=dtype, fill_value=value, name="s") graph, lib, _ = nnvm.compiler.build(s, target) m = graph_runtime.create(graph, lib, ctx) m.run() out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) tvm.testing.assert_allclose( out.asnumpy(), np.full(shape, fill_value=value, dtype=dtype), atol=1e-5, rtol=1e-5) # ones s = sym.ones(shape=shape, dtype=dtype, name="s") graph, lib, _ = nnvm.compiler.build(s, target) m = graph_runtime.create(graph, lib, ctx) m.run() out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) tvm.testing.assert_allclose( out.asnumpy(), np.full(shape, fill_value=1, dtype=dtype), atol=1e-5, rtol=1e-5) # zeros s = sym.zeros(shape=shape, dtype=dtype, name="s") graph, lib, _ = nnvm.compiler.build(s, target) m = graph_runtime.create(graph, lib, ctx) m.run() out = m.get_output(0, tvm.nd.empty(shape, dtype=dtype)) tvm.testing.assert_allclose( out.asnumpy(), np.full(shape, fill_value=0, dtype=dtype), atol=1e-5, rtol=1e-5)