numpy.product - python examples

Here are the examples of the python api numpy.product taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

145 Examples 7

3 View Complete Implementation : model.py
Copyright Apache License 2.0
Author : google
  def set_model_params(self, model_params):
    pointer = 0
    for i in range(len(self.shapes)):
      w_shape = self.shapes[i]
      b_shape = self.shapes[i][1]
      s_w = np.product(w_shape)
      s = s_w + b_shape
      chunk = np.array(model_params[pointer:pointer+s])
      self.weight[i] = chunk[:s_w].reshape(w_shape)
      self.bias[i] = chunk[s_w:].reshape(b_shape)
      pointer += s

3 View Complete Implementation : model.py
Copyright Apache License 2.0
Author : google
  def set_model_params(self, model_params):
    pointer = 0
    for i in range(len(self.shapes)):
      w_shape = self.shapes[i]
      b_shape = self.shapes[i][1]
      s_w = np.product(w_shape)
      s = s_w + b_shape
      chunk = np.array(model_params[pointer:pointer+s])
      self.weight[i] = chunk[:s_w].reshape(w_shape)
      self.bias[i] = chunk[s_w:].reshape(b_shape)
      pointer += s
      if self.output_noise[i]:
        s = b_shape
        self.bias_log_std[i] = np.array(model_params[pointer:pointer+s])
        self.bias_std[i] = np.exp(self.sigma_factor*self.bias_log_std[i] + self.sigma_bias)
        if self.render_mode:
          print("bias_std, layer", i, self.bias_std[i])
        pointer += s

3 View Complete Implementation : model_grid_near.py
Copyright Apache License 2.0
Author : google
  def set_model_params(self, model_params):
    pointer = 0
    for i in range(len(self.shapes)):
      w_shape = self.shapes[i]
      b_shape = self.shapes[i][1]
      s_w = np.product(w_shape)
      s = s_w + b_shape
      chunk = np.array(model_params[pointer:pointer+s])
      self.weight[i] = chunk[:s_w].reshape(w_shape)
      self.bias[i] = chunk[s_w:].reshape(b_shape)
      pointer += s

3 View Complete Implementation : model.py
Copyright Apache License 2.0
Author : google
  def set_model_params(self, model_params):
    pointer = 0
    for i in range(len(self.shapes)):
      w_shape = self.shapes[i]
      b_shape = self.shapes[i][1]
      s_w = np.product(w_shape)
      s = s_w + b_shape
      chunk = np.array(model_params[pointer:pointer+s])
      self.weight[i] = chunk[:s_w].reshape(w_shape)
      self.bias[i] = chunk[s_w:].reshape(b_shape)
      pointer += s

3 View Complete Implementation : nn.py
Copyright Apache License 2.0
Author : google
  def set_model_params(self, model_params):
    pointer = 0
    for i in range(len(self.shapes)):
      w_shape = self.shapes[i]
      b_shape = self.shapes[i][1]
      s_w = np.product(w_shape)
      s = s_w + b_shape
      chunk = np.array(model_params[pointer:pointer+s])
      self.weight[i] = chunk[:s_w].reshape(w_shape)
      self.bias[i] = chunk[s_w:].reshape(b_shape)
      pointer += s
    # rnn states
    s = self.hidden_size
    self.init_h = model_params[pointer:pointer+s].reshape((1, self.hidden_size))
    self.h = self.init_h
    self.rnn = RNNCell(self.input_size, self.weight[0], self.bias[0])

3 View Complete Implementation : mio4.py
Copyright MIT License
Author : ktraunmueller
    def write_char(self, arr, name):
        arr = arr_to_chars(arr)
        arr = arr_to_2d(arr, self.oned_as)
        dims = arr.shape
        self.write_header(
            name,
            dims,
            P=miUINT8,
            T=mxCHAR_CLast)
        if arr.dtype.kind == 'U':
            # Recode unicode to latin1
            n_chars = np.product(dims)
            st_arr = np.ndarray(shape=(),
                                dtype=arr_dtype_number(arr, n_chars),
                                buffer=arr)
            st = st_arr.item().encode('latin-1')
            arr = np.ndarray(shape=dims, dtype='S1', buffer=st)
        self.write_bytes(arr)

3 View Complete Implementation : mio4.py
Copyright MIT License
Author : ktraunmueller
    def write_char(self, arr, name):
        arr = arr_to_chars(arr)
        arr = arr_to_2d(arr, self.oned_as)
        dims = arr.shape
        self.write_header(
            name,
            dims,
            P=miUINT8,
            T=mxCHAR_CLast)
        if arr.dtype.kind == 'U':
            # Recode unicode to latin1
            n_chars = np.product(dims)
            st_arr = np.ndarray(shape=(),
                                dtype=arr_dtype_number(arr, n_chars),
                                buffer=arr)
            st = st_arr.item().encode('latin-1')
            arr = np.ndarray(shape=dims, dtype='S1', buffer=st)
        self.write_bytes(arr)

3 View Complete Implementation : model_grid_fc.py
Copyright Apache License 2.0
Author : google
  def set_model_params(self, model_params):
    pointer = 0
    for i in range(len(self.shapes)):
      w_shape = self.shapes[i]
      b_shape = self.shapes[i][1]
      s_w = np.product(w_shape)
      s = s_w + b_shape
      chunk = np.array(model_params[pointer:pointer+s])
      self.weight[i] = chunk[:s_w].reshape(w_shape)
      self.bias[i] = chunk[s_w:].reshape(b_shape)
      pointer += s

3 View Complete Implementation : model.py
Copyright Apache License 2.0
Author : google
  def set_model_params(self, model_params):
    pointer = 0
    for i in range(len(self.shapes)):
      w_shape = self.shapes[i]
      b_shape = self.shapes[i][1]
      s_w = np.product(w_shape)
      s = s_w + b_shape
      chunk = np.array(model_params[pointer:pointer+s])
      self.weight[i] = chunk[:s_w].reshape(w_shape)
      self.bias[i] = chunk[s_w:].reshape(b_shape)
      pointer += s
    # rnn states
    s = self.hidden_size
    self.init_h = model_params[pointer:pointer+s].reshape((1, self.hidden_size))
    pointer += s
    self.init_c = model_params[pointer:pointer+s].reshape((1, self.hidden_size))

    self.reset_state()
    self.lstm = LSTMCell(self.obs_size + self.action_size, self.weight[0], self.bias[0], dropout_keep_prob=self.dropout_keep_prob, train_mode=self.train_mode)

3 View Complete Implementation : test_multiarray_assignment.py
Copyright MIT License
Author : ktraunmueller
def _check_astignment(srcidx, dstidx):
    """Check astignment arr[dstidx] = arr[srcidx] works."""

    arr = np.arange(np.product(shape)).reshape(shape)

    cpy = arr.copy()

    cpy[dstidx] = arr[srcidx]
    arr[dstidx] = arr[srcidx]

    astert np.all(arr == cpy), 'astigning arr[%s] = arr[%s]' % (dstidx, srcidx)